1 code implementation • 13 Apr 2024 • Kateryna Chumachenko, Alexandros Iosifidis, Moncef Gabbouj
Within the field of multimodal DFER, recent methods have focused on exploiting advances of self-supervised learning (SSL) for pre-training of strong multimodal encoders.
Ranked #1 on Dynamic Facial Expression Recognition on MAFW
Dynamic Facial Expression Recognition Facial Expression Recognition +2
no code implementations • 16 Mar 2024 • Farhad Pakdaman, Moncef Gabbouj
The emerging Learned Compression (LC) replaces the traditional codec modules with Deep Neural Networks (DNN), which are trained end-to-end for rate-distortion performance.
no code implementations • 9 Feb 2024 • Muhammad Uzair Zahid, Aysen Degerli, Fahad Sohrab, Serkan Kiranyaz, Tahir Hamid, Rashid Mazhar, Moncef Gabbouj
Early detection of myocardial infarction (MI), a critical condition arising from coronary artery disease (CAD), is vital to prevent further myocardial damage.
no code implementations • 8 Feb 2024 • Yuxin Xie, Li Yu, Farhad Pakdaman, Moncef Gabbouj
Noisy images are a challenge to image compression algorithms due to the inherent difficulty of compressing noise.
no code implementations • 5 Feb 2024 • Farhad Pakdaman, Sanaz Nami, Moncef Gabbouj
Emerging Learned image Compression (LC) achieves significant improvements in coding efficiency by end-to-end training of neural networks for compression.
no code implementations • 5 Feb 2024 • Umut Cem Entok, Firas Laakom, Farhad Pakdaman, Moncef Gabbouj
Motivated by this, we propose a novel multi-illuminant color constancy method, by learning pixel-wise illumination maps caused by multiple light sources.
no code implementations • 5 Feb 2024 • Li Yu, Yanjun Gao, Farhad Pakdaman, Moncef Gabbouj
In response to these challenges, we propose a panoramic image inpainting framework that consists of a Face Generator, a Cube Generator, a side branch, and two discriminators.
1 code implementation • 3 Feb 2024 • Lei Xu, Moncef Gabbouj
In particular, the proposed framework containing a cGANs and a novel auxiliary network is developed to enhance and stabilize the generator's performance under two alternative training stages, when estimating a multiscale probability feature map from heterogeneous and imbalanced inputs iteratively.
no code implementations • 3 Feb 2024 • Tanveer Khan, Fahad Sohrab, Antonis Michalas, Moncef Gabbouj
In this study, we use various OCC models for $\mathbb{X}$ user classification.
1 code implementation • 29 Jan 2024 • Lei Xu, Mete Ahishali, Moncef Gabbouj
Deep learning-based informative band selection methods on hyperspectral images (HSI) recently have gained intense attention to eliminate spectral correlation and redundancies.
1 code implementation • 6 Jan 2024 • Ali Falahati, Mohammad Karim Safavi, Ardavan Elahi, Farhad Pakdaman, Moncef Gabbouj
Providing high-quality video with efficient bitrate is a main challenge in video industry.
no code implementations • 5 Jan 2024 • Firas Laakom, Yuheng Bu, Moncef Gabbouj
Existing generalization theories of supervised learning typically take a holistic approach and provide bounds for the expected generalization over the whole data distribution, which implicitly assumes that the model generalizes similarly for all the classes.
no code implementations • 2 Jan 2024 • Mohammad Al-Sa'd, Tuomas Jalonen, Serkan Kiranyaz, Moncef Gabbouj
Diagnosis of bearing faults is paramount to reducing maintenance costs and operational breakdowns.
no code implementations • 17 Dec 2023 • Serkan Kiranyaz, Ozer Can Devecioglu, Amir Alhams, Sadok Sassi, Turker Ince, Onur Avci, Moncef Gabbouj
One major reason is the lack of a benchmark dataset providing a large volume of both vibration and sound data over several working conditions for different machines and sensor locations.
no code implementations • 30 Nov 2023 • Tuomas Jalonen, Mohammad Al-Sa'd, Serkan Kiranyaz, Moncef Gabbouj
Detection of rolling-element bearing faults is crucial for implementing proactive maintenance strategies and for minimizing the economic and operational consequences of unexpected failures.
no code implementations • 16 Nov 2023 • Kateryna Chumachenko, Alexandros Iosifidis, Moncef Gabbouj
Interestingly, we also observe that optimization of the unimodal branches improves the multimodal branch, compared to a similar multimodal model trained from scratch.
no code implementations • 2 Oct 2023 • Quoc Minh Nguyen, Dat Thanh Tran, Juho Kanniainen, Alexandros Iosifidis, Moncef Gabbouj
Many cryptocurrency brokers nowadays offer a variety of derivative assets that allow traders to perform hedging or speculation.
no code implementations • 27 Sep 2023 • Ilke Adalioglu, Mete Ahisali, Aysen Degerli, Serkan Kiranyaz, Moncef Gabbouj
Myocardial infarction (MI) is a severe case of coronary artery disease (CAD) and ultimately, its detection is substantial to prevent progressive damage to the myocardium.
no code implementations • 26 Sep 2023 • Zaffar Zaffar, Fahad Sohrab, Juho Kanniainen, Moncef Gabbouj
The study highlights the potential of subspace learning-based OCC algorithms by investigating the limitations of current fraud detection strategies and the specific challenges of credit card fraud detection.
no code implementations • 25 Sep 2023 • Firas Laakom, Fahad Sohrab, Jenni Raitoharju, Alexandros Iosifidis, Moncef Gabbouj
We show that such regularizers improve performance.
no code implementations • 25 Sep 2023 • Fahad Sohrab, Firas Laakom, Moncef Gabbouj
The objective of S-SVDD is to map the original data to a subspace optimized for one-class classification, and the iterative optimization process of data mapping and description in S-SVDD relies on gradient descent.
no code implementations • 25 Sep 2023 • Jake Guidry, Fahad Sohrab, Raju Gottumukkala, Satya Katragadda, Moncef Gabbouj
Research has been done on the efficacy of these methods, most notably One-Class Support Vector Machine and Support Vector Data Description, but many new extensions of these works have been proposed and have yet to be tested for injection attacks in vehicular networks.
1 code implementation • 12 Jul 2023 • Mete Ahishali, Mehmet Yamac, Serkan Kiranyaz, Moncef Gabbouj
In this work, we propose a novel approach called Operational Support Estimator Networks (OSENs) for the support estimation task.
no code implementations • ICLR Workshop EBM 2021 • Firas Laakom, Jenni Raitoharju, Alexandros Iosifidis, Moncef Gabbouj
Energy-based learning is a powerful learning paradigm that encapsulates various discriminative and generative approaches.
1 code implementation • IEEE Signal Processing Letters 2023 • Li Yu, Junyang Li, Farhad Pakdaman, Miaogen Ling, Moncef Gabbouj
No-Reference Image Quality Assessment aims to evaluate the perceptual quality of an image, according to human perception.
no code implementations • 19 Apr 2023 • Ozer Can Devecioglu, Mete Ahishali, Fahad Sohrab, Turker Ince, Moncef Gabbouj
As a consequence of global warming and climate change, the risk and extent of wildfires have been increasing in many areas worldwide.
no code implementations • 19 Apr 2023 • Sertac Kilickaya, Mete Ahishali, Fahad Sohrab, Turker Ince, Moncef Gabbouj
Considering the imbalanced labels of the LULC classification problem and rich spectral information (high number of dimensions), the proposed classification approach is well-suited for HSI data.
1 code implementation • 17 Apr 2023 • Adamantios Ntakaris, Moncef Gabbouj, Juho Kanniainen
This high-paced stock price forecasting is usually based on vectors that need to be treated as sequential and time-independent signals due to the time irregularities that are inherent in high-frequency trading.
1 code implementation • 29 Mar 2023 • Alexander Ulrichsen, Paul Murray, Stephen Marshall, Moncef Gabbouj, Serkan Kiranyaz, Mehmet Yamac, Nour Aburaed
This work focuses on extending the convolutional filters of a popular super-resolution model to more powerful operational filters to enhance the model performance on hyperspectral images.
1 code implementation • 19 Mar 2023 • Kang Liao, Lang Nie, Shujuan Huang, Chunyu Lin, Jing Zhang, Yao Zhao, Moncef Gabbouj, DaCheng Tao
In this paper, we provide a comprehensive survey of learning-based camera calibration techniques, by analyzing their strengths and limitations.
no code implementations • 23 Feb 2023 • Tuomas Jalonen, Mohammad Al-Sa'd, Roope Mellanen, Serkan Kiranyaz, Moncef Gabbouj
The health and safety hazards posed by worn crane lifting ropes mandate periodic inspection for damage.
no code implementations • 3 Jan 2023 • Firas Laakom, Jenni Raitoharju, Alexandros Iosifidis, Moncef Gabbouj
At each optimization step, neurons at a given layer receive feedback from neurons belonging to higher layers of the hierarchy.
1 code implementation • 30 Dec 2022 • Turker Ince, Serkan Kiranyaz, Ozer Can Devecioglu, Muhammad Salman Khan, Muhammad Chowdhury, Moncef Gabbouj
In this study, we propose a novel approach for blind restoration of real-world audio signals by Operational Generative Adversarial Networks (Op-GANs) with temporal and spectral objective metrics to enhance the quality of restored audio signal regardless of the type and severity of each artifact corrupting it.
1 code implementation • 12 Dec 2022 • Serkan Kiranyaz, Ozer Can Devecioglu, Amir Alhams, Sadok Sassi, Turker Ince, Osama Abdeljaber, Onur Avci, Moncef Gabbouj
To address this need, in this pilot study, we propose a zero-shot bearing fault detection method that can detect any fault on a new (target) machine regardless of the working conditions, sensor parameters, or fault characteristics.
no code implementations • 25 Oct 2022 • Li Yu, Wenshuai Chang, Shiyu Wu, Moncef Gabbouj
In this work, we propose a transformer-based compressed video quality enhancement (TVQE) method, consisting of Swin-AutoEncoder based Spatio-Temporal feature Fusion (SSTF) module and Channel-wise Attention based Quality Enhancement (CAQE) module.
1 code implementation • 29 Sep 2022 • Mete Ahishali, Aysen Degerli, Serkan Kiranyaz, Tahir Hamid, Rashid Mazhar, Moncef Gabbouj
The proposed restoration approach achieves over 90% F1-Score which is significantly higher than the performance of any deep model.
no code implementations • 22 Sep 2022 • Firas Laakom, Jenni Raitoharju, Alexandros Iosifidis, Moncef Gabbouj
In this paper, we propose an approach that builds on top of BoF pooling to boost its efficiency by ensuring that the items of the learned dictionary are non-redundant.
1 code implementation • 14 Jul 2022 • Mehmet Yamaç, Mert Duman, İlke Adalıoğlu, Serkan Kiranyaz, Moncef Gabbouj
An extensive set of experiments performed on the benchmark MIT-BIH ECG dataset shows that when this domain adaptation-based training data generator is used with a simple 1-D CNN classifier, the method outperforms the prior work by a significant margin.
Ranked #2 on Arrhythmia Detection on MIT-BIH Arrhythmia Database
no code implementations • 14 Apr 2022 • Aysen Degerli, Fahad Sohrab, Serkan Kiranyaz, Moncef Gabbouj
In this study, we propose a framework for early detection of MI over multi-view echocardiography that leverages one-class classification (OCC) techniques.
no code implementations • 7 Apr 2022 • Muhammad Uzair Zahid, Serkan Kiranyaz, Moncef Gabbouj
The classification layers can thus benefit from both temporal and learned features for the final arrhythmia classification.
no code implementations • 21 Feb 2022 • Aysen Degerli, Serkan Kiranyaz, Muhammad E. H. Chowdhury, Moncef Gabbouj
To address the data scarcity encountered in training and especially in evaluation, this study extends the largest COVID-19 CXR dataset: QaTa-COV19 with 121, 378 CXRs including 9258 COVID-19 samples with their corresponding ground-truth segmentation masks that are publicly shared with the research community.
1 code implementation • 20 Feb 2022 • Mete Ahishali, Serkan Kiranyaz, Iftikhar Ahmad, Moncef Gabbouj
The band selection in the hyperspectral image (HSI) data processing is an important task considering its effect on the computational complexity and accuracy.
no code implementations • 9 Feb 2022 • Firas Laakom, Jenni Raitoharju, Nikolaos Passalis, Alexandros Iosifidis, Moncef Gabbouj
In this paper, we consider the problem of non-linear dimensionality reduction under uncertainty, both from a theoretical and algorithmic perspectives.
no code implementations • 9 Feb 2022 • Firas Laakom, Jenni Raitoharju, Alexandros Iosifidis, Moncef Gabbouj
We tested our approach across different tasks: dimensionality reduction using three different dataset, image compression using the MNIST dataset, and image denoising using fashion MNIST.
2 code implementations • 29 Jan 2022 • Serkan Kiranyaz, Ozer Can Devecioglu, Turker Ince, Junaid Malik, Muhammad Chowdhury, Tahir Hamid, Rashid Mazhar, Amith Khandakar, Anas Tahir, Tawsifur Rahman, Moncef Gabbouj
Usually, a set of such artifacts occur on the same ECG signal with varying severity and duration, and this makes an accurate diagnosis by machines or medical doctors extremely difficult.
1 code implementation • 26 Jan 2022 • Kateryna Chumachenko, Alexandros Iosifidis, Moncef Gabbouj
In this paper, we consider the problem of multimodal data analysis with a use case of audiovisual emotion recognition.
Ranked #1 on Facial Emotion Recognition on RAVDESS
no code implementations • 26 Jan 2022 • Kateryna Chumachenko, Alexandros Iosifidis, Moncef Gabbouj
In this work, we propose several attention formulations for multivariate sequence data.
no code implementations • 29 Nov 2021 • Junaid Malik, Serkan Kiranyaz, Moncef Gabbouj
As the integration of non-local information is known to benefit denoising, in this work we investigate the use of super neurons for both synthetic and real-world image denoising.
1 code implementation • 10 Nov 2021 • Firas Laakom, Kateryna Chumachenko, Jenni Raitoharju, Alexandros Iosifidis, Moncef Gabbouj
Based on this idea, we propose to reformulate the attention mechanism in CNNs to learn to ignore instead of learning to attend.
1 code implementation • 10 Nov 2021 • Firas Laakom, Jenni Raitoharju, Jarno Nikkanen, Alexandros Iosifidis, Moncef Gabbouj
We test this approach on the proposed method and show that it can indeed be used to avoid several extreme error cases and, thus, improves the practicality of the proposed technique.
1 code implementation • 9 Nov 2021 • Aysen Degerli, Serkan Kiranyaz, Tahir Hamid, Rashid Mazhar, Moncef Gabbouj
Following the blockage of a coronary artery, the regional wall motion abnormality (RWMA) of the ischemic myocardial segments is the earliest change to set in.
1 code implementation • 30 Sep 2021 • Moncef Gabbouj, Serkan Kiranyaz, Junaid Malik, Muhammad Uzair Zahid, Turker Ince, Muhammad Chowdhury, Amith Khandakar, Anas Tahir
Although numerous R-peak detectors have been proposed in the literature, their robustness and performance levels may significantly deteriorate in low-quality and noisy signals acquired from mobile electrocardiogram (ECG) sensors, such as Holter monitors.
no code implementations • 30 Sep 2021 • Turker Ince, Junaid Malik, Ozer Can Devecioglu, Serkan Kiranyaz, Onur Avci, Levent Eren, Moncef Gabbouj
Preventive maintenance of modern electric rotating machinery (RM) is critical for ensuring reliable operation, preventing unpredicted breakdowns and avoiding costly repairs.
no code implementations • 30 Sep 2021 • Junaid Malik, Ozer Can Devecioglu, Serkan Kiranyaz, Turker Ince, Moncef Gabbouj
Despite the proliferation of numerous deep learning methods proposed for generic ECG classification and arrhythmia detection, compact systems with the real-time ability and high accuracy for classifying patient-specific ECG are still few.
no code implementations • 29 Sep 2021 • Firas Laakom, Jenni Raitoharju, Alexandros Iosifidis, Moncef Gabbouj
Neural networks are composed of multiple layers arranged in a hierarchical structure jointly trained with a gradient-based optimization, where the errors are back-propagated from the last layer back to the first one.
no code implementations • 28 Sep 2021 • Ozer Can Devecioglu, Junaid Malik, Turker Ince, Serkan Kiranyaz, Eray Atalay, Moncef Gabbouj
Glaucoma leads to permanent vision disability by damaging the optical nerve that transmits visual images to the brain.
no code implementations • 2 Sep 2021 • Dat Thanh Tran, Moncef Gabbouj, Alexandros Iosifidis
By developing compressive sensing and learning models that can operate with an adaptive compression rate, we can maximize the informational content throughput of the whole application.
1 code implementation • 1 Sep 2021 • Dat Thanh Tran, Juho Kanniainen, Moncef Gabbouj, Alexandros Iosifidis
Data normalization is one of the most important preprocessing steps when building a machine learning model, especially when the model of interest is a deep neural network.
no code implementations • 4 Aug 2021 • Mehmet Yamac, Ugur Akpinar, Erdem Sahin, Serkan Kiranyaz, Moncef Gabbouj
For a special case where the CS operation is set as a single tensor multiplication, the model is reduced to the learning-based separable CS; while a dense CS matrix can be approximated and learned as the summation of multiple tensors.
no code implementations • 3 Aug 2021 • Serkan Kiranyaz, Junaid Malik, Mehmet Yamac, Mert Duman, Ilke Adalioglu, Esin Guldogan, Turker Ince, Moncef Gabbouj
In this article, we present superior (generative) neuron models (or super neurons in short) that allow random or learnable kernel shifts and thus can increase the receptive field size of each connection.
2 code implementations • 27 Jun 2021 • Mete Ahishali, Mehmet Yamac, Serkan Kiranyaz, Moncef Gabbouj
To the best of our knowledge, this is the first representation-based method proposed for performing a regression task by utilizing the modified CSENs; and hence, we name this novel approach as Representation-based Regression (RbR).
no code implementations • 10 Jun 2021 • Firas Laakom, Jenni Raitoharju, Alexandros Iosifidis, Moncef Gabbouj
We study the diversity of the features learned by a two-layer neural network trained with the least squares loss.
1 code implementation • 8 May 2021 • Kaitai Zhang, Bin Wang, Wei Wang, Fahad Sohrab, Moncef Gabbouj, C. -C. Jay Kuo
An image anomaly localization method based on the successive subspace learning (SSL) framework, called AnomalyHop, is proposed in this work.
1 code implementation • 29 Apr 2021 • Fahad Sohrab, Alexandros Iosifidis, Moncef Gabbouj, Jenni Raitoharju
In this paper, we propose a novel subspace learning framework for one-class classification.
1 code implementation • 31 Mar 2021 • Dat Thanh Tran, Moncef Gabbouj, Alexandros Iosifidis
Knowledge Distillation refers to a class of methods that transfers the knowledge from a teacher network to a student network.
no code implementations • 4 Mar 2021 • Junaid Malik, Serkan Kiranyaz, Mehmet Yamac, Moncef Gabbouj
Despite their recent success on image denoising, the need for deep and complex architectures still hinders the practical usage of CNNs.
1 code implementation • 4 Mar 2021 • Junaid Malik, Serkan Kiranyaz, Mehmet Yamac, Esin Guldogan, Moncef Gabbouj
Real-world blind denoising poses a unique image restoration challenge due to the non-deterministic nature of the underlying noise distribution.
no code implementations • 9 Feb 2021 • Kateryna Chumachenko, Jenni Raitoharju, Alexandros Iosifidis, Moncef Gabbouj
In this paper, we propose a method for ensembling the outputs of multiple object detectors for improving detection performance and precision of bounding boxes on image data.
no code implementations • 28 Jan 2021 • Aysen Degerli, Mete Ahishali, Serkan Kiranyaz, Muhammad E. H. Chowdhury, Moncef Gabbouj
To address this need, in this study, we propose a reliable COVID-19 detection network: ReCovNet, which can discriminate COVID-19 pneumonia from 14 different thoracic diseases and healthy subjects.
no code implementations • 1 Jan 2021 • Firas Laakom, Jenni Raitoharju, Alexandros Iosifidis, Moncef Gabbouj
During the last decade, neural networks have been intensively used to tackle various problems and they have often led to state-of-the-art results.
no code implementations • 29 Dec 2020 • Muhammad Uzair Zahid, Serkan Kiranyaz, Turker Ince, Ozer Can Devecioglu, Muhammad E. H. Chowdhury, Amith Khandakar, Anas Tahir, Moncef Gabbouj
Results also demonstrate similar or better performance than most competing algorithms on MIT-DB with 99. 83% F1-score, 99. 85% recall, and 99. 82% precision.
no code implementations • 23 Nov 2020 • Mohammad Soltanian, Junaid Malik, Jenni Raitoharju, Alexandros Iosifidis, Serkan Kiranyaz, Moncef Gabbouj
Automatic classification of speech commands has revolutionized human computer interactions in robotic applications.
no code implementations • 10 Nov 2020 • Mete Ahishali, Serkan Kiranyaz, Turker Ince, Moncef Gabbouj
In this work, to address the limitations of traditional ML and deep CNN based methods, a novel and systematic classification framework is proposed for the classification of PolSAR images, based on a compact and adaptive implementation of CNNs using a sliding-window classification approach.
no code implementations • 5 Oct 2020 • Aysen Degerli, Morteza Zabihi, Serkan Kiranyaz, Tahir Hamid, Rashid Mazhar, Ridha Hamila, Moncef Gabbouj
Myocardial infarction (MI), or commonly known as heart attack, is a life-threatening health problem worldwide from which 32. 4 million people suffer each year.
no code implementations • 26 Sep 2020 • Aysen Degerli, Mete Ahishali, Mehmet Yamac, Serkan Kiranyaz, Muhammad E. H. Chowdhury, Khalid Hameed, Tahir Hamid, Rashid Mazhar, Moncef Gabbouj
To accomplish this, we have compiled the largest dataset with 119, 316 CXR images including 2951 COVID-19 samples, where the annotation of the ground-truth segmentation masks is performed on CXRs by a novel collaborative human-machine approach.
no code implementations • 22 Sep 2020 • Dat Thanh Tran, Moncef Gabbouj, Alexandros Iosifidis
Recently, the Multilinear Compressive Learning (MCL) framework was proposed to efficiently optimize the sensing and learning steps when working with multidimensional signals, i. e. tensors.
no code implementations • 1 Sep 2020 • Junaid Malik, Serkan Kiranyaz, Moncef Gabbouj
Convolutional Neural Networks (CNNs) have recently become a favored technique for image denoising due to its adaptive learning ability, especially with a deep configuration.
no code implementations • 1 Sep 2020 • Firas Laakom, Jenni Raitoharju, Nikolaos Passalis, Alexandros Iosifidis, Moncef Gabbouj
spectral-based subspace learning is a common data preprocessing step in many machine learning pipelines.
no code implementations • 29 Aug 2020 • Junaid Malik, Serkan Kiranyaz, Moncef Gabbouj
Discriminative learning based on convolutional neural networks (CNNs) aims to perform image restoration by learning from training examples of noisy-clean image pairs.
no code implementations • 28 Aug 2020 • Jorge Peña Queralta, Jussi Taipalmaa, Bilge Can Pullinen, Victor Kathan Sarker, Tuan Nguyen Gia, Hannu Tenhunen, Moncef Gabbouj, Jenni Raitoharju, Tomi Westerlund
Autonomous or teleoperated robots have been playing increasingly important roles in civil applications in recent years.
no code implementations • 21 Aug 2020 • Serkan Kiranyaz, Junaid Malik, Habib Ben Abdallah, Turker Ince, Alexandros Iosifidis, Moncef Gabbouj
As a heterogenous network model, ONNs are based on a generalized neuron model that can encapsulate any set of non-linear operators to boost diversity and to learn highly complex and multi-modal functions or spaces with minimal network complexity and training data.
no code implementations • 11 Aug 2020 • Serkan Kiranyaz, Aysen Degerli, Tahir Hamid, Rashid Mazhar, Rayyan Ahmed, Rayaan Abouhasera, Morteza Zabihi, Junaid Malik, Ridha Hamila, Moncef Gabbouj
It further enables medical experts to gain an enhanced visualization capability of echo images through color-coded segments along with their "maximum motion displacement" plots helping them to better assess wall motion and LV Ejection-Fraction (LVEF).
no code implementations • 20 Jul 2020 • Firas Laakom, Jenni Raitoharju, Alexandros Iosifidis, Jarno Nikkanen, Moncef Gabbouj
Computational color constancy is a preprocessing step used in many camera systems.
1 code implementation • 7 Jun 2020 • Mete Ahishali, Aysen Degerli, Mehmet Yamac, Serkan Kiranyaz, Muhammad E. H. Chowdhury, Khalid Hameed, Tahir Hamid, Rashid Mazhar, Moncef Gabbouj
The detection of COVID-19 in early stages is not a straightforward task from chest X-ray images according to expert medical doctors because the traces of the infection are visible only when the disease has progressed to a moderate or severe stage.
1 code implementation • 3 Jun 2020 • Junaid Malik, Serkan Kiranyaz, Moncef Gabbouj
Operational Neural Networks (ONNs) have recently been proposed as a special class of artificial neural networks for grid structured data.
1 code implementation • 25 May 2020 • Dat Thanh Tran, Nikolaos Passalis, Anastasios Tefas, Moncef Gabbouj, Alexandros Iosifidis
In this paper, we propose 2D-Attention (2DA), a generic attention formulation for sequence data, which acts as a complementary computation block that can detect and focus on relevant sources of information for the given learning objective.
1 code implementation • 21 May 2020 • Farhad Pakdaman, Mohammad Ali Adelimanesh, Moncef Gabbouj, Mahmoud Reza Hashemi
While the next generation video compression standard, Versatile Video Coding (VVC), provides a superior compression efficiency, its computational complexity dramatically increases.
Multimedia Computational Complexity Image and Video Processing
no code implementations • 8 May 2020 • Mehmet Yamac, Mete Ahishali, Aysen Degerli, Serkan Kiranyaz, Muhammad E. H. Chowdhury, Moncef Gabbouj
Any technological tool that can be provided to healthcare practitioners to save time, effort, and possibly lives has crucial importance.
no code implementations • 6 May 2020 • Firas Laakom, Jenni Raitoharju, Alexandros Iosifidis, Uygar Tuna, Jarno Nikkanen, Moncef Gabbouj
In this paper, we propose a novel unsupervised color constancy method, called Probabilistic Color Constancy (PCC).
2 code implementations • 24 Apr 2020 • Serkan Kiranyaz, Junaid Malik, Habib Ben Abdallah, Turker Ince, Alexandros Iosifidis, Moncef Gabbouj
However, Greedy Iterative Search (GIS) method, which is the search method used to find optimal operators in ONNs takes many training sessions to find a single operator set per layer.
no code implementations • 9 Apr 2020 • Onur Avci, Osama Abdeljaber, Serkan Kiranyaz, Mohammed Hussein, Moncef Gabbouj, Daniel J. Inman
Monitoring structural damage is extremely important for sustaining and preserving the service life of civil structures.
no code implementations • 8 Apr 2020 • Lei Xu, Jenni Raitoharju, Alexandros Iosifidis, Moncef Gabbouj
The proposed method is based on a probabilistic model for defining the weights of individual samples in a weighted multi-label LDA approach.
no code implementations • 25 Mar 2020 • Ali Senhaji, Jenni Raitoharju, Moncef Gabbouj, Alexandros Iosifidis
The most common approach in multi-domain learning is to form a domain agnostic model, the parameters of which are shared among all domains, and learn a small number of extra domain-specific parameters for each individual new domain.
1 code implementation • 20 Mar 2020 • Fahad Sohrab, Jenni Raitoharju, Alexandros Iosifidis, Moncef Gabbouj
In this paper, we propose a novel method for transforming data into a low-dimensional space optimized for one-class classification.
no code implementations • 2 Mar 2020 • Mehmet Yamac, Mete Ahishali, Serkan Kiranyaz, Moncef Gabbouj
Indeed, a vast majority of them use sparse signal recovery techniques to obtain support sets instead of directly mapping the non-zero locations from denser measurements (e. g., Compressively Sensed Measurements).
1 code implementation • 17 Feb 2020 • Dat Thanh Tran, Moncef Gabbouj, Alexandros Iosifidis
Progressive Neural Network Learning is a class of algorithms that incrementally construct the network's topology and optimize its parameters based on the training data.
1 code implementation • 17 Feb 2020 • Dat Thanh Tran, Moncef Gabbouj, Alexandros Iosifidis
Extensive experiments demonstrate that the proposed knowledge transfer method can effectively train MCL models to compressively sense and synthesize better features for the learning tasks with improved performances, especially when the complexity of the learning task increases.
no code implementations • 11 Feb 2020 • Kateryna Chumachenko, Jenni Raitoharju, Moncef Gabbouj, Alexandros Iosifidis
This paper proposes an incremental solution to Fast Subclass Discriminant Analysis (fastSDA).
no code implementations • 5 Feb 2020 • Johanna Ärje, Claus Melvad, Mads Rosenhøj Jeppesen, Sigurd Agerskov Madsen, Jenni Raitoharju, Maria Strandgård Rasmussen, Alexandros Iosifidis, Ville Tirronen, Kristian Meissner, Moncef Gabbouj, Toke Thomas Høye
We use this database to test the classification accuracy i. e. how well the species identity of a specimen can be predicted from images taken by the machine.
1 code implementation • 23 Oct 2019 • Firas Laakom, Jenni Raitoharju, Alexandros Iosifidis, Jarno Nikkanen, Moncef Gabbouj
In this paper, we describe a new large dataset for illumination estimation.
Few-Shot Camera-Adaptive Color Constancy Image Declipping +1
no code implementations • 6 Sep 2019 • Ali Bahrami Rad, Morteza Zabihi, Zheng Zhao, Moncef Gabbouj, Aggelos K. Katsaggelos, Simo Särkkä
Results: The proposed algorithm is validated on the 2018 PhysioNet challenge dataset.
no code implementations • 19 Aug 2019 • Anton Muravev, Jenni Raitoharju, Moncef Gabbouj
Our matrix of probabilities is equivalent to the population of models, but allows for discovery of structural irregularities, while being simple to interpret and analyze.
no code implementations • 13 Jul 2019 • Adamantios Ntakaris, Juho Kanniainen, Moncef Gabbouj, Alexandros Iosifidis
Stock price prediction is a challenging task, but machine learning methods have recently been used successfully for this purpose.
no code implementations • 20 Jun 2019 • Mehmet Yamac, Mete Ahishali, Nikolaos Passalis, Jenni Raitoharju, Bulent Sankur, Moncef Gabbouj
Security monitoring via ubiquitous cameras and their more extended in intelligent buildings stand to gain from advances in signal processing and machine learning.
1 code implementation • 11 Jun 2019 • Firas Laakom, Nikolaos Passalis, Jenni Raitoharju, Jarno Nikkanen, Anastasios Tefas, Alexandros Iosifidis, Moncef Gabbouj
To further improve the illumination estimation accuracy, we propose a novel attention mechanism for the BoCF model with two variants based on self-attention.
no code implementations • 4 Jun 2019 • Firas Laakom, Jenni Raitoharju, Alexandros Iosifidis, Jarno Nikkanen, Moncef Gabbouj
In this paper, we study the importance of pre-training for the generalization capability in the color constancy problem.
2 code implementations • 17 May 2019 • Dat Thanh Tran, Mehmet Yamac, Aysen Degerli, Moncef Gabbouj, Alexandros Iosifidis
Compressive Learning is an emerging topic that combines signal acquisition via compressive sensing and machine learning to perform inference tasks directly on a small number of measurements.
no code implementations • 9 May 2019 • Serkan Kiranyaz, Onur Avci, Osama Abdeljaber, Turker Ince, Moncef Gabbouj, Daniel J. Inman
During the last decade, Convolutional Neural Networks (CNNs) have become the de facto standard for various Computer Vision and Machine Learning operations.
1 code implementation • IEEE Transactions on Neural Networks and Learning Systems 2019 • Dat Thanh Tran, Alexandros Iosifidis, Juho Kanniainen, Moncef Gabbouj
Financial time-series forecasting has long been a challenging problem because of the inherently noisy and stochastic nature of the market.
1 code implementation • 2 May 2019 • Kateryna Chumachenko, Jenni Raitoharju, Alexandros Iosifidis, Moncef Gabbouj
We show that by exploiting the structure of the between-class Laplacian matrix, the eigendecomposition step can be substituted with a much faster process.
1 code implementation • 16 Apr 2019 • Fahad Sohrab, Jenni Raitoharju, Alexandros Iosifidis, Moncef Gabbouj
In this paper, we propose a novel method for projecting data from multiple modalities to a new subspace optimized for one-class classification.
no code implementations • 10 Apr 2019 • Adamantios Ntakaris, Giorgio Mirone, Juho Kanniainen, Moncef Gabbouj, Alexandros Iosifidis
Mid-price movement prediction based on limit order book (LOB) data is a challenging task due to the complexity and dynamics of the LOB.
no code implementations • 9 Apr 2019 • Junaid Malik, Serkan Kiranyaz, Riyadh Al-Raoush, Olivier Monga, Patricia Garnier, Sebti Foufou, Abdelaziz Bouras, Alexandros Iosifidis, Moncef Gabbouj, Philippe C. Baveye
Binary segmentation of volumetric images of porous media is a crucial step towards gaining a deeper understanding of the factors governing biogeochemical processes at minute scales.
no code implementations • 27 Mar 2019 • Junaid Malik, Serkan Kiranyaz, Suchitra Kunhoth, Turker Ince, Somaya Al-Maadeed, Ridha Hamila, Moncef Gabbouj
Moreover, we conduct quantitative comparative evaluations among the traditional methods, transfer learning-based methods and the proposed adaptive approach for the particular task of cancer detection and identification from scarce and low-resolution histology images.
no code implementations • 5 Mar 2019 • Dat Thanh Tran, Juho Kanniainen, Moncef Gabbouj, Alexandros Iosifidis
Forecasting based on financial time-series is a challenging task since most real-world data exhibits nonstationary property and nonlinear dependencies.
no code implementations • 1 Mar 2019 • Morteza Zabihi, Ali Bahrami Rad, Serkan Kiranyaz, Simo Särkkä, Moncef Gabbouj
Sleep arousals transition the depth of sleep to a more superficial stage.
3 code implementations • 21 Feb 2019 • Nikolaos Passalis, Anastasios Tefas, Juho Kanniainen, Moncef Gabbouj, Alexandros Iosifidis
Deep Learning (DL) models can be used to tackle time series analysis tasks with great success.
no code implementations • 15 Feb 2019 • Serkan Kiranyaz, Turker Ince, Alexandros Iosifidis, Moncef Gabbouj
In order to address this drawback and also to accomplish a more generalized model over the convolutional neurons, this study proposes a novel network model, called Operational Neural Networks (ONNs), which can be heterogeneous and encapsulate neurons with any set of operators to boost diversity and to learn highly complex and multi-modal functions or spaces with minimal network complexity and training data.
no code implementations • 24 Jan 2019 • Nikolaos Passalis, Anastasios Tefas, Juho Kanniainen, Moncef Gabbouj, Alexandros Iosifidis
However, combining existing BoF formulations with deep feature extractors pose significant challenges: the distribution of the input features is not stationary, tuning the hyper-parameters of the model can be especially difficult and the normalizations involved in the BoF model can cause significant instabilities during the training process.
no code implementations • 23 Oct 2018 • Avraam Tsantekidis, Nikolaos Passalis, Anastasios Tefas, Juho Kanniainen, Moncef Gabbouj, Alexandros Iosifidis
The recent surge in Deep Learning (DL) research of the past decade has successfully provided solutions to many difficult problems.
no code implementations • 15 Oct 2018 • Aysen Degerli, Sinem Aslan, Mehmet Yamac, Bulent Sankur, Moncef Gabbouj
Recent literature works show that compressive image classification is possible in CS domain without reconstruction of the signal.
no code implementations • 19 Sep 2018 • Paraskevi Nousi, Avraam Tsantekidis, Nikolaos Passalis, Adamantios Ntakaris, Juho Kanniainen, Anastasios Tefas, Moncef Gabbouj, Alexandros Iosifidis
Forecasting the movements of stock prices is one the most challenging problems in financial markets analysis.
no code implementations • 10 Sep 2018 • Honglei Zhang, Serkan Kiranyaz, Moncef Gabbouj
In this paper, we propose an evolutionary strategy to find better topologies for deep CNNs.
1 code implementation • 20 Aug 2018 • Dat Thanh Tran, Serkan Kiranyaz, Moncef Gabbouj, Alexandros Iosifidis
Generalized Operational Perceptron (GOP) was proposed to generalize the linear neuron model in the traditional Multilayer Perceptron (MLP) and this model can mimic the synaptic connections of the biological neurons that have nonlinear neurochemical behaviours.
1 code implementation • 13 Apr 2018 • Dat Thanh Tran, Serkan Kiranyaz, Moncef Gabbouj, Alexandros Iosifidis
Previously, Generalized Operational Perceptron (GOP) was proposed to extend conventional perceptron model by defining a diverse set of neuronal activities to imitate a generalized model of biological neurons.
no code implementations • 19 Feb 2018 • Lei Xu, Alexandros Iosifidis, Moncef Gabbouj
In this paper, we propose a new variant of Linear Discriminant Analysis to overcome underlying drawbacks of traditional LDA and other LDA variants targeting problems involving imbalanced classes.
1 code implementation • 12 Feb 2018 • Fahad Sohrab, Jenni Raitoharju, Moncef Gabbouj, Alexandros Iosifidis
The method iteratively optimizes the data mapping along with data description in order to define a compact class representation in a low-dimensional feature space.
no code implementations • 31 Jan 2018 • Guanqun Cao, Alexandros Iosifidis, Moncef Gabbouj, Vijay Raghavan, Raju Gottumukkala
We study the problem of learning to rank from multiple information sources.
1 code implementation • 4 Dec 2017 • Dat Thanh Tran, Alexandros Iosifidis, Juho Kanniainen, Moncef Gabbouj
Financial time-series forecasting has long been a challenging problem because of the inherently noisy and stochastic nature of the market.
no code implementations • 29 Oct 2017 • Dat Thanh Tran, Moncef Gabbouj, Alexandros Iosifidis
There has been a great effort to transfer linear discriminant techniques that operate on vector data to high-order data, generally referred to as Multilinear Discriminant Analysis (MDA) techniques.
no code implementations • 28 Sep 2017 • Dat Thanh Tran, Alexandros Iosifidis, Moncef Gabbouj
The excellent performance of deep neural networks has enabled us to solve several automatization problems, opening an era of autonomous devices.
no code implementations • 5 Sep 2017 • Dat Thanh Tran, Martin Magris, Juho Kanniainen, Moncef Gabbouj, Alexandros Iosifidis
Nowadays, with the availability of massive amount of trade data collected, the dynamics of the financial markets pose both a challenge and an opportunity for high frequency traders.
no code implementations • 31 Aug 2017 • Guanqun Cao, Alexandros Iosifidis, Moncef Gabbouj
Face verification is a problem approached in the literature mainly using nonlinear class-specific subspace learning techniques.
no code implementations • 23 Aug 2017 • Johanna Ärje, Jenni Raitoharju, Alexandros Iosifidis, Ville Tirronen, Kristian Meissner, Moncef Gabbouj, Serkan Kiranyaz, Salme Kärkkäinen
Contrary to previous findings in the literature, we find that for machines following a typical flat classification approach commonly used in machine learning performs better than forcing machines to adopt a hierarchical, local per parent node approach used by human taxonomic experts ($\overline{CE}=13. 8\%$).
no code implementations • 21 Mar 2017 • Caglar Aytekin, Jarno Nikkanen, Moncef Gabbouj
In this paper, we provide a novel dataset designed for camera invariant color constancy research.
1 code implementation • 6 Dec 2016 • Francesco Cricri, Xingyang Ni, Mikko Honkala, Emre Aksu, Moncef Gabbouj
Thanks to the recurrent connections, the decoder can exploit temporal summaries generated from all layers of the encoder.
no code implementations • 13 Sep 2016 • Caglar Aytekin, Alexandros Iosifidis, Moncef Gabbouj
In this paper, we model the salient object detection problem under a probabilistic framework encoding the boundary connectivity saliency cue and smoothness constraints in an optimization problem.
no code implementations • 21 Jun 2016 • Honglei Zhang, Jenni Raitoharju, Serkan Kiranyaz, Moncef Gabbouj
Graph clustering is an important technique to understand the relationships between the vertices in a big graph.
Social and Information Networks Physics and Society
no code implementations • 31 May 2016 • Guanqun Cao, Alexandros Iosifidis, Ke Chen, Moncef Gabbouj
In this paper, the problem of multi-view embedding from different visual cues and modalities is considered.
no code implementations • 9 Feb 2015 • Rama Garimella, Berkay Kicanaoglu, Moncef Gabbouj
In this research paper novel real/complex valued recurrent Hopfield Neural Network (RHNN) is proposed.