no code implementations • 28 Mar 2024 • Kilian Carolan, Laura Fennelly, Alan F. Smeaton
Large Language Models (LLMs) have recently emerged as a focal point of research and application, driven by their unprecedented ability to understand and generate text with human-like quality.
no code implementations • 27 Jan 2024 • Xiao Liu, Alessandra Mileo, Alan F. Smeaton
In-situ monitoring incorporating data from visual and other sensor technologies, allows the collection of extensive datasets during the Additive Manufacturing (AM) process.
no code implementations • 11 Jan 2024 • Ly-Duyen Tran, Cathal Gurrin, Alan F. Smeaton
Personal data includes the digital footprints that we leave behind as part of our everyday activities, both online and offline in the real world.
no code implementations • 27 Nov 2023 • Ayush K. Rai, Tarun Krishna, Feiyan Hu, Alexandru Drimbarean, Kevin McGuinness, Alan F. Smeaton, Noel E. O'Connor
Video Anomaly Detection (VAD) is an open-set recognition task, which is usually formulated as a one-class classification (OCC) problem, where training data is comprised of videos with normal instances while test data contains both normal and anomalous instances.
no code implementations • 10 Nov 2023 • Siddhant Jaydeep Mahajani, Shashank Srivastava, Alan F. Smeaton
Our findings are that the importance of a word depends on the domain and there are no standout lexical entries which systematically cause differences in sentiment scores.
no code implementations • 21 Sep 2023 • Vaibhav Mudgal, Qingyang Wang, Lorin Sweeney, Alan F. Smeaton
Video memorability is a measure of how likely a particular video is to be remembered by a viewer when that viewer has no emotional connection with the video content.
no code implementations • 21 Sep 2023 • Aniket Jagtap, RamaKrishna Venkatesh Saripalli, Joe Lemley, Waseem Shariff, Alan F. Smeaton
Ground-truth HR measurements obtained using conventional methods were used to evaluate of the accuracy of automatic detection of HR from event camera data.
no code implementations • 14 Sep 2023 • Iya Chivileva, Philip Lynch, Tomas E. Ward, Alan F. Smeaton
The contribution is an assessment of commonly used quality metrics, and a comparison of their performances and the performance of human evaluations on an open dataset of T2V videos.
no code implementations • 16 Aug 2023 • Lorin Sweeney, Graham Healy, Alan F. Smeaton
In a world of ephemeral moments, our brain diligently sieves through a cascade of experiences, like a skilled gold prospector searching for precious nuggets amidst the river's relentless flow.
no code implementations • 16 Jul 2023 • Hamza Riaz, Alan F. Smeaton
Domain generalisation involves pooling knowledge from source domain(s) into a single model that can generalise to unseen target domain(s).
no code implementations • 14 Jul 2023 • Xiao Liu, Alessandra Mileo, Alan F. Smeaton
The development of computer vision and in-situ monitoring using visual sensors allows the collection of large datasets from the additive manufacturing (AM) process.
no code implementations • 16 Jun 2023 • Colin Hehir, Alan F. Smeaton
The matrix profile (MP) is a data structure computed from a time series which encodes the data required to locate motifs and discords, corresponding to recurring patterns and outliers respectively.
no code implementations • 9 May 2023 • Deniss Strods, Alan F. Smeaton
Audio regeneration is translated into image regeneration by transforming audio into a Mel-spectrogram and using image in-painting to regenerate the gaps.
no code implementations • 11 Mar 2023 • Hitesh Raju, Ankit Sharma, Aoife Smeaton, Alan F. Smeaton
This work is a step towards automatic alerting of the likely onset of an epileptic seizure from the signalling behaviour of a trained assistance dog.
no code implementations • 17 Jan 2023 • Hamza Riaz, Alan F. Smeaton
Often, when we train a model on a dataset in one specific domain and test on another unseen domain known as an out of distribution (OOD) dataset, models or ML tools show a decrease in performance.
no code implementations • 19 Dec 2022 • Lorin Sweeney, Graham Healy, Alan F. Smeaton
As part of the MediaEval 2022 Predicting Video Memorability task we explore the relationship between visual memorability, the visual representation that characterises it, and the underlying concept portrayed by that visual representation.
no code implementations • 19 Dec 2022 • Dinh Viet Cuong, Phuc H. Le-Khac, Adam Stapleton, Elke Eichlemann, Mark Roantree, Alan F. Smeaton
In this work we focus on gap filling in air quality data where the task is to predict the AQI at 1, 5 and 7 days into the future.
no code implementations • 13 Dec 2022 • Lorin Sweeney, Mihai Gabriel Constantin, Claire-Hélène Demarty, Camilo Fosco, Alba G. Seco de Herrera, Sebastian Halder, Graham Healy, Bogdan Ionescu, Ana Matran-Fernandez, Alan F. Smeaton, Mushfika Sultana
This paper describes the 5th edition of the Predicting Video Memorability Task as part of MediaEval2022.
no code implementations • 12 Dec 2022 • Xiao Liu, Alan F. Smeaton, Alessandra Mileo
More specifically, this paper will look at two scenarios: firstly, using convolutional neural networks (CNNs) to automatically inspect and classify emission data collected by in-situ monitoring and secondly, applying Active Learning techniques to the developed classification model to construct a human-in-the-loop mechanism in order to accelerate the labeling process of the emission data.
no code implementations • 7 Dec 2022 • Alba García Deco de Herrera, Mihai Gabriel Constantin, Chaire-Hélène Demarty, Camilo Fosco, Sebastian Halder, Graham Healy, Bogdan Ionescu, Ana Matran-Fernandez, Alan F. Smeaton, Mushfika Sultana, Lorin Sweeney
The Predicting Media Memorability task in the MediaEval evaluation campaign has been running annually since 2018 and several different tasks and data sets have been used in this time.
1 code implementation • 11 Oct 2022 • Ayush K. Rai, Tarun Krishna, Julia Dietlmeier, Kevin McGuinness, Alan F. Smeaton, Noel E. O'Connor
In this work, we address this issue by revisiting a simple and effective self-supervised method and augment it with a differentiable motion feature learning module to tackle the spatial and temporal diversities in the GEBD task.
no code implementations • 8 Aug 2022 • Victoria Rhodes, Maureen Maguire, Meghana Shetty, Conor McAloon, Alan F. Smeaton
Circadian rhythms are a process of the sleep-wake cycle that regulates the physical, mental and behavioural changes in all living beings with a period of roughly 24 h. Wearable accelerometers are typically used in livestock applications to record animal movement from which we can estimate the activity type.
no code implementations • 6 Aug 2022 • Sean Cummins, Lorin Sweeney, Alan F. Smeaton
We investigate the memorability of a 5-season span of a popular crime-drama TV series, CSI, through the application of a vision transformer fine-tuned on the task of predicting video memorability.
1 code implementation • 25 Jul 2022 • Tarun Krishna, Ayush K. Rai, Yasser A. D. Djilali, Alan F. Smeaton, Kevin McGuinness, Noel E. O'Connor
Currently, convnets pre-trained with self-supervision have obtained comparable performance on downstream tasks in comparison to their supervised counterparts in computer vision.
no code implementations • 28 Jun 2022 • Alan F. Smeaton, Aparajita Dey-Plissonneau, Hyowon Lee, Mingming Liu, Michael Scriney
Second language learning can be enabled by tandem collaboration where students are grouped into video conference calls while learning the native language of other student(s) on the calls.
no code implementations • 15 Dec 2021 • Lorin Sweeney, Graham Healy, Alan F. Smeaton
This paper describes our approach to the Predicting Media Memorability task in MediaEval 2021, which aims to address the question of media memorability by setting the task of automatically predicting video memorability.
no code implementations • 11 Dec 2021 • Rukiye Savran Kiziltepe, Mihai Gabriel Constantin, Claire-Helene Demarty, Graham Healy, Camilo Fosco, Alba Garcia Seco de Herrera, Sebastian Halder, Bogdan Ionescu, Ana Matran-Fernandez, Alan F. Smeaton, Lorin Sweeney
This paper describes the MediaEval 2021 Predicting Media Memorability}task, which is in its 4th edition this year, as the prediction of short-term and long-term video memorability remains a challenging task.
no code implementations • 4 Dec 2021 • Rukiye Savran Kiziltepe, Lorin Sweeney, Mihai Gabriel Constantin, Faiyaz Doctor, Alba Garcia Seco de Herrera, Claire-Helene Demarty, Graham Healy, Bogdan Ionescu, Alan F. Smeaton
Data includes the reaction times for each recognition of each video.
no code implementations • 30 Nov 2021 • Andrew Merrigan, Alan F. Smeaton
Images posted online present a privacy concern in that they may be used as reference examples for a facial recognition system.
no code implementations • 29 Nov 2021 • Joe Kinahan, Alan F. Smeaton
There is a marked increase in delivery services in urban areas, and with Jeff Bezos claiming that 86% of the orders that Amazon ships weigh less than 5 lbs, the time is ripe for investigation into economical methods of automating the final stage of the delivery process.
no code implementations • 16 Nov 2021 • Alan F. Smeaton
Computer vision and multimedia information processing have made extreme progress within the last decade and many tasks can be done with a level of accuracy as if done by humans, or better.
no code implementations • 16 Nov 2021 • Aparajita Dey-Plissonneau, Hyowon Lee, Michael Scriney, Alan F. Smeaton, Vincent Pradier, Hamza Riaz
This pilot study focuses on a tool called L2L that allows second language (L2) learners to visualise and analyse their Zoom interactions with native speakers.
1 code implementation • 16 Jun 2021 • Luka Murn, Saverio Blasi, Alan F. Smeaton, Marta Mrak
The approach requires a single neural network to be trained from which a full quarter-pixel interpolation filter set is derived, as the network is easily interpretable due to its linear structure.
1 code implementation • MoTra (NoDaLiDa) 2021 • Lifeng Han, Gareth J. F. Jones, Alan F. Smeaton
To facilitate effective translation modeling and translation studies, one of the crucial questions to address is how to assess translation quality.
1 code implementation • 27 Apr 2021 • George Awad, Asad A. Butt, Keith Curtis, Jonathan Fiscus, Afzal Godil, Yooyoung Lee, Andrew Delgado, Jesse Zhang, Eliot Godard, Baptiste Chocot, Lukas Diduch, Jeffrey Liu, Alan F. Smeaton, Yvette Graham, Gareth J. F. Jones, Wessel Kraaij, Georges Quenot
In total, 29 teams from various research organizations worldwide completed one or more of the following six tasks: 1.
no code implementations • 23 Apr 2021 • Lorin Sweeney, Graham Healy, Alan F. Smeaton
We introduce a novel multimodal deep learning-based late-fusion system that uses audio gestalt to estimate the influence of a given video's audio on its overall short-term recognition memorability, and selectively leverages audio features to make a prediction accordingly.
1 code implementation • NoDaLiDa 2021 • Lifeng Han, Gareth J. F. Jones, Alan F. Smeaton, Paolo Bolzoni
To investigate the impact of Chinese decomposition embedding in detail, i. e., radical, stroke, and intermediate levels, and how well these decompositions represent the meaning of the original character sequences, we carry out analysis with both automated and human evaluation of MT.
no code implementations • 9 Feb 2021 • Marc Górriz, Saverio Blasi, Alan F. Smeaton, Noel E. O'Connor, Marta Mrak
Simplifications include a framework for reducing the overhead of the convolutional operations, a simplified cross-component processing model integrated into the original architecture, and a methodology to perform integer-precision approximations with the aim to obtain fast and hardware-aware implementations.
no code implementations • 27 Jan 2021 • Rashmiranjan Das, Gaurav Negi, Alan F. Smeaton
This involves replacing the face of an individual from a source video with the face of a second person, in the destination video.
no code implementations • 15 Jan 2021 • Hyowon Lee, Mingming Liu, Hamza Riaz, Navaneethan Rajasekaren, Michael Scriney, Alan F. Smeaton
We can also factor in other criteria into video summary generation such as parts where the student was not paying attention while others in the class were, and parts of the video that other students have replayed extensively which a given student has not.
no code implementations • 31 Dec 2020 • Phuc H. Le-Khac, Ayush K. Rai, Graham Healy, Alan F. Smeaton, Noel E. O'Connor
The Predicting Media Memorability task in MediaEval'20 has some challenging aspects compared to previous years.
no code implementations • 31 Dec 2020 • Alba García Seco De Herrera, Rukiye Savran Kiziltepe, Jon Chamberlain, Mihai Gabriel Constantin, Claire-Hélène Demarty, Faiyaz Doctor, Bogdan Ionescu, Alan F. Smeaton
This paper describes the MediaEval 2020 \textit{Predicting Media Memorability} task.
no code implementations • 31 Dec 2020 • Lorin Sweeney, Graham Healy, Alan F. Smeaton
Memorability determines what evanesces into emptiness, and what worms its way into the deepest furrows of our minds.
no code implementations • 10 Nov 2020 • Simranjeet Singh, Rajneesh Sharma, Alan F. Smeaton
There are many applications of Generative Adversarial Networks (GANs) in fields like computer vision, natural language processing, speech synthesis, and more.
no code implementations • 10 Oct 2020 • Phuc H. Le-Khac, Graham Healy, Alan F. Smeaton
Examples of how contrastive learning has been applied in computer vision, natural language processing, audio processing, and others, as well as in Reinforcement Learning are also presented.
1 code implementation • 5 Oct 2020 • David Azcona, Kevin McGuinness, Alan F. Smeaton
Overall we achieved a performance of 93. 4% AUC on the validation data by using the more recent deep learning architectures and data augmentation strategies.
no code implementations • 21 Sep 2020 • George Awad, Asad A. Butt, Keith Curtis, Yooyoung Lee, Jonathan Fiscus, Afzal Godil, Andrew Delgado, Jesse Zhang, Eliot Godard, Lukas Diduch, Alan F. Smeaton, Yvette Graham, Wessel Kraaij, Georges Quenot
The TREC Video Retrieval Evaluation (TRECVID) 2019 was a TREC-style video analysis and retrieval evaluation, the goal of which remains to promote progress in research and development of content-based exploitation and retrieval of information from digital video via open, metrics-based evaluation.
no code implementations • 4 Aug 2020 • Alan F. Smeaton, Swathikiran Srungavarapu, Cyril Messaraa, Claire Tansey
Materials and Methods: 12 women aged 30 to 60 years participated in a product trial and had close-up images of the cheek and temple regions of their faces taken with a high-resolution Antera 3D CS camera at the start and end of a 4-week period.
no code implementations • 31 Jul 2020 • Feiyan Hu, Venkatesh G M, Noel E. O'Connor, Alan F. Smeaton, Suzanne Little
We investigate: 1) How a visual attention map such as a \emph{subjectness} attention or saliency map and an \emph{objectness} attention map can facilitate region proposal generation in a 2-stage object detector; 2) How a visual attention map can be used for tracking multiple objects.
no code implementations • 27 Jun 2020 • Marc Górriz, Saverio Blasi, Alan F. Smeaton, Noel E. O'Connor, Marta Mrak
Neural networks can be used in video coding to improve chroma intra-prediction.
1 code implementation • 11 Jun 2020 • Luka Murn, Saverio Blasi, Alan F. Smeaton, Noel E. O'Connor, Marta Mrak
Deep learning has shown great potential in image and video compression tasks.
1 code implementation • LREC 2020 • Lifeng Han, Gareth J. F. Jones, Alan F. Smeaton
The only bilingual MWE corpora that we are aware of is from the PARSEME (PARSing and Multi-word Expressions) EU Project.
no code implementations • 30 Mar 2020 • Eoin Brophy, Willie Muehlhausen, Alan F. Smeaton, Tomas E. Ward
These same sampling frequencies also yielded a robust heart rate estimation which was comparative with that achieved at the more energy-intensive rate of 256 Hz.
1 code implementation • 5 Mar 2020 • Zhengwei Wang, Qi She, Alan F. Smeaton, Tomas E. Ward, Graham Healy
In this work, we introduce an evaluation metric called Neuroscore, for evaluating the performance of GANs, that more directly reflects psychoperceptual image quality through the utilization of brain signals.
1 code implementation • 26 Aug 2019 • Marc Górriz, Marta Mrak, Alan F. Smeaton, Noel E. O'Connor
In this work recent advances in conditional adversarial networks are investigated to develop an end-to-end architecture based on Convolutional Neural Networks (CNNs) to directly map realistic colours to an input greyscale image.
no code implementations • 28 May 2019 • Zhengwei Wang, Qi She, Eoin Brophy, Alan F. Smeaton, Tomas E. Ward, Graham Healy
Deep neural networks (DNNs) are inspired from the human brain and the interconnection between the two has been widely studied in the literature.
1 code implementation • 10 May 2019 • Zhengwei Wang, Qi She, Alan F. Smeaton, Tomas E. Ward, Graham Healy
In this work, we describe an evaluation metric we call Neuroscore, for evaluating the performance of GANs, that more directly reflects psychoperceptual image quality through the utilization of brain signals.
no code implementations • 15 Jan 2019 • Zhengwei Wang, Graham Healy, Alan F. Smeaton, Tomas E. Ward
In this paper we make two primary contributions to that field: 1) We propose a novel spatial filtering method which we call the Multiple Time Window LDA Beamformer (MTWLB) method; 2) we provide a comprehensive comparison of nine spatial filtering pipelines using three spatial filtering schemes namely, MTWLB, xDAWN, Common Spatial Pattern (CSP) and three linear classification methods Linear Discriminant Analysis (LDA), Bayesian Linear Regression (BLR) and Logistic Regression (LR).
no code implementations • 3 Dec 2018 • Eoin Brophy, José Juan Dominguez Veiga, Zhengwei Wang, Alan F. Smeaton, Tomas E. Ward
We then use the 2048 dimensional features from the penultimate layer as input to a support vector machine.
no code implementations • 10 Nov 2018 • Zhengwei Wang, Graham Healy, Alan F. Smeaton, Tomas E. Ward
We propose a novel approach that combines a brain-computer interface (BCI) with GANs to generate a measure we call Neuroscore, which closely mirrors the behavioral ground truth measured from participants tasked with discerning real from synthetic images.
no code implementations • 9 Apr 2015 • Eva Mohedano, Amaia Salvador, Sergi Porta, Xavier Giró-i-Nieto, Graham Healy, Kevin McGuinness, Noel O'Connor, Alan F. Smeaton
We show that it is indeed possible to detect such objects in complex images and, also, that users with previous knowledge on the dataset or experience with the RSVP outperform others.
no code implementations • 19 Aug 2014 • Eva Mohedano, Graham Healy, Kevin McGuinness, Xavier Giro-i-Nieto, Noel E. O'Connor, Alan F. Smeaton
This paper explores the potential of brain-computer interfaces in segmenting objects from images.
no code implementations • Computer Vision and Pattern Recognition 2007 • Ciaran´ O Conaire, Noel E. O’Connor, Alan F. Smeaton
Traditional methods for creating classifiers have two main disadvantages.