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 • 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.
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.
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.
no code implementations • 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 • 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 • 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 • 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.