no code implementations • 2 Jun 2024 • Sulaiman Khan, Md. Rafiul Biswas, Alina Murad, Hazrat Ali, Zubair Shah
We also identify key limitations associated with the early investigation study on MLLMs for specialized tasks in medical image analysis.
1 code implementation • IEEE Transactions on Image Processing 2024 • Anas Zafar, Danyal Aftab, Rizwan Qureshi, Xinqi Fan, Pingjun Chen, Jia Wu, Hazrat Ali, Shah Nawaz, Sheheryar Khan, Mubarak Shah
In this paper, we propose a novel and computationally efficient architecture Single Stage Adaptive Multi-Attention Network (SSAMAN) for image restoration tasks, particularly for image denoising and image deblurring.
Ranked #1 on Image Denoising on DND
no code implementations • 6 Sep 2023 • Hazrat Ali, Farida Mohsen, Zubair Shah
This review provides valuable insights for researchers in the field of AI and healthcare to advance the state-of-the-art in lung cancer diagnosis and prognosis.
no code implementations • 7 Apr 2023 • Hazrat Ali, Christer Gronlund, Zubair Shah
These recommendations might be useful to improve acceptability for the GAN-based approaches for data augmentation as GANs for data augmentation are increasingly becoming popular in the AI and medical imaging research community.
1 code implementation • 4 Dec 2022 • Usama Tariq, Rizwan Qureshi, Anas Zafar, Danyal Aftab, Jia Wu, Tanvir Alam, Zubair Shah, Hazrat Ali
Furthermore, the model can generate high-quality synthetic brain MRI with a tumor that can limit the small sample size issues.
no code implementations • 2 Nov 2022 • Hazrat Ali, Shafaq Murad, Zubair Shah
In this work, we explore the possibilities of synthesis of medical images using neural diffusion models.
no code implementations • 23 Oct 2022 • Farida Mohsen, Hazrat Ali, Nady El Hajj, Zubair Shah
Specifically, early fusion was the most used technique in most applications for multimodal learning (22 out of 34 studies).
no code implementations • 28 Sep 2022 • Hazrat Ali
We present the use of machine learning methods to perform detection of Urdu text from the scene images.
no code implementations • 19 Aug 2022 • Sofia Kanwal, Sohail Asghar, Hazrat Ali
Robust speech emotion recognition relies on the quality of the speech features.
no code implementations • 6 Jun 2022 • Owais Ali, Hazrat Ali, Syed Ayaz Ali Shah, Aamir Shahzad
We selected U-Net because, in medical image segmentation, U-Net is a prominent model that provides improved performance for medical image segmentation even if the dataset size is small.
no code implementations • 3 Jun 2022 • Mehreen Mubashar, Hazrat Ali, Christer Gronlund, Shoaib Azmat
The problem can be ascribed to its simple feature extracting blocks: encoder/decoder, and the semantic gap between encoder and decoder.
no code implementations • 15 May 2022 • Hazrat Ali, Zubair Shah
This review included 57 full-text studies that reported the use of GANs for different applications in COVID-19 lungs images data.
no code implementations • 16 Sep 2021 • Hazrat Ali, Khalid Iqbal, Ghulam Mujtaba, Ahmad Fayyaz, Mohammad Farhad Bulbul, Fazal Wahab Karam, Ali Zahir
To the best of our knowledge, the work is the first of its kind for the Urdu language and would provide a good dataset for free research use and serve as a baseline performance on the task of Urdu text extraction.
no code implementations • 10 May 2021 • Muhammad Shakaib Iqbal, Hazrat Ali, Son N. Tran, Talha Iqbal
Food resources face severe damages under extraordinary situations of catastrophes such as earthquakes, cyclones, and tsunamis.
no code implementations • 23 Sep 2020 • Hazrat Ali, Johannes Umander, Robin Rohlén, Christer Grönlund
In this work, we present an alternative method - a deep learning pipeline - to identify active MUs in ultrasound image sequences, including segmentation of their territories and signal estimation of their mechanical responses (twitch train).
no code implementations • 12 Sep 2020 • Faizan Munawar, Shoaib Azmat, Talha Iqbal, Christer Grönlund, Hazrat Ali
In our work, the generator of the GAN is trained to generate a segmented mask of a given input CXR.
1 code implementation • 21 Feb 2020 • Waqar Ahmad, Misbah Kazmi, Hazrat Ali
Achieving high accuracy by traditional machine learning algorithms, (such as SVM, KNN and random forest method) is a challenging task because the data acquired from the wearable sensors like accelerometer and gyroscope is a time-series data.
no code implementations • 17 Dec 2019 • Hazrat Ali, Ahsan Ullah, Talha Iqbal, Shahid Khattak
More specifically, we use a two-layer and a three-layer deep autoencoder network and convolutional neural network and evaluate the two frameworks in terms of recognition accuracy.
no code implementations • 13 Dec 2019 • Hazrat Ali, Feroz Karim, Junaid Javed Qureshi, Adnan Omer Abuassba, Mohammad Farhad Bulbul
The purpose of this work is to investigate the application of bidirectional LSTM for seizure prediction.
no code implementations • 30 Jul 2019 • Kashif Sultan, Hazrat Ali, Haris Anwaar, Kabo Poloko Nkabiti, Adeel Ahamd, Zhongshan Zhang
The internet activity records (IARs) of a mobile cellular network posses significant information which can be exploited to identify the network's efficacy and the mobile users' behavior.
no code implementations • 27 May 2019 • Sulaiman Khan, Hazrat Ali, Zia Ullah, Mohammad Farhad Bulbul
The proposed method uses an HD (High Definition) camera mounted on the road side either on a pole or on a traffic signal for recording video frames.
no code implementations • 6 Apr 2019 • Sulaiman Khan, Hazrat Ali, Zahid Ullah, Nasru Minallah, Shahid Maqsood, Abdul Hafeez
This paper presents a recognition system for handwritten Pashto letters.
no code implementations • 19 Mar 2019 • Mohammad Farhad Bulbul, Saiful Islam, Hazrat Ali
We then characterize the action video by extracting the Gradient Local Auto-Correlations (GLAC) features from the SHIs and the MHIs.
1 code implementation • 1 Oct 2018 • Talha Iqbal, Hazrat Ali
The proposed model achieves a dice coefficient of 0. 837 on STARE dataset and 0. 832 on DRIVE dataset which is state-of-the-art performance on both the datasets.
no code implementations • 2 Aug 2018 • Hazrat Ali, Adnan Ali Awan, Sanaullah Khan, Omer Shafique, Atiq ur Rahman, Shahid Khan
In this study gray-scale images are used for training the classification model.
no code implementations • 30 Jul 2018 • Kashif Sultan, Hazrat Ali, Zhongshan Zhang
By passing anomaly and anomaly-free data through this model, we observe the effect of anomalous activities in training of the model and also observe mean square error of anomaly and anomaly free data.