Search Results for author: Alan F. Smeaton

Found 63 papers, 12 papers with code

A Review of Multi-Modal Large Language and Vision Models

no code implementations28 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.

Image Captioning Prompt Engineering +2

A Systematic Review of Available Datasets in Additive Manufacturing

no code implementations27 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.

Defect Detection

Lifelogging As An Extreme Form of Personal Information Management -- What Lessons To Learn

no code implementations11 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.

Benchmarking Management

Video Anomaly Detection via Spatio-Temporal Pseudo-Anomaly Generation : A Unified Approach

no code implementations27 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.

One-Class Classification Open Set Learning +2

A Comparison of Lexicon-Based and ML-Based Sentiment Analysis: Are There Outlier Words?

no code implementations10 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.

Sentiment Analysis

Using Saliency and Cropping to Improve Video Memorability

no code implementations21 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.


Heart Rate Detection Using an Event Camera

no code implementations21 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.

Measuring the Quality of Text-to-Video Model Outputs: Metrics and Dataset

no code implementations14 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.

Memories in the Making: Predicting Video Memorability with Encoding Phase EEG

no code implementations16 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.


Domain Generalisation with Bidirectional Encoder Representations from Vision Transformers

no code implementations16 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).

Defect Classification in Additive Manufacturing Using CNN-Based Vision Processing

no code implementations14 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.

Active Learning

Calculating the matrix profile from noisy data

no code implementations16 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.

Time Series

Enhancing Gappy Speech Audio Signals with Generative Adversarial Networks

no code implementations9 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.

Automatic Detection of Signalling Behaviour from Assistance Dogs as they Forecast the Onset of Epileptic Seizures in Humans

no code implementations11 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.

Vision Based Machine Learning Algorithms for Out-of-Distribution Generalisation

no code implementations17 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.

Domain Adaptation object-detection +3

Diffusing Surrogate Dreams of Video Scenes to Predict Video Memorability

no code implementations19 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.

An adaptive human-in-the-loop approach to emission detection of Additive Manufacturing processes and active learning with computer vision

no code implementations12 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.

Active Learning Transfer Learning

Experiences from the MediaEval Predicting Media Memorability Task

no code implementations7 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.

Motion Aware Self-Supervision for Generic Event Boundary Detection

1 code implementation11 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.

Boundary Detection Generic Event Boundary Detection

Periodicity Intensity of the 24 h Circadian Rhythm in Newborn Calves Show Indicators of Herd Welfare

no code implementations8 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.

Analysing the Memorability of a Procedural Crime-Drama TV Series, CSI

no code implementations6 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.


Dynamic Channel Selection in Self-Supervised Learning

1 code implementation25 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.

Image Classification Self-Supervised Learning

Analysis of Individual Conversational Volatility in Tandem Telecollaboration for Second Language Learning

no code implementations28 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.

Predicting Media Memorability: Comparing Visual, Textual and Auditory Features

no code implementations15 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.

Overview of The MediaEval 2021 Predicting Media Memorability Task

no code implementations11 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.


Using a GAN to Generate Adversarial Examples to Facial Image Recognition

no code implementations30 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.

Face Recognition Generative Adversarial Network +1

Image Segmentation to Identify Safe Landing Zones for Unmanned Aerial Vehicles

no code implementations29 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.

Image Segmentation Semantic Segmentation

Computer Vision for Supporting Image Search

no code implementations16 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.

Image Retrieval

Facilitating reflection in teletandem through automatically generated conversation metrics and playback video

no code implementations16 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.

Improved CNN-based Learning of Interpolation Filters for Low-Complexity Inter Prediction in Video Coding

1 code implementation16 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.

Explainable Models Motion Compensation +1

Translation Quality Assessment: A Brief Survey on Manual and Automatic Methods

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.

Machine Translation Natural Language Understanding +3

The Influence of Audio on Video Memorability with an Audio Gestalt Regulated Video Memorability System

no code implementations23 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.

Multimodal Deep Learning Video Recognition

Chinese Character Decomposition for Neural MT with Multi-Word Expressions

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.

Machine Translation Translation

Attention-Based Neural Networks for Chroma Intra Prediction in Video Coding

no code implementations9 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.

Detecting Deepfake Videos Using Euler Video Magnification

no code implementations27 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.

Face Swapping

Attention Based Video Summaries of Live Online Zoom Classes

no code implementations15 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.

Investigating Memorability of Dynamic Media

no code implementations31 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.

Leveraging Audio Gestalt to Predict Media Memorability

no code implementations31 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.

Multimodal Deep Learning

Using GANs to Synthesise Minimum Training Data for Deepfake Generation

no code implementations10 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.

Face Swapping Image Generation +1

Contrastive Representation Learning: A Framework and Review

no code implementations10 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.

BIG-bench Machine Learning Contrastive Learning +2

A Comparative Study of Existing and New Deep Learning Methods for Detecting Knee Injuries using the MRNet Dataset

1 code implementation5 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.

Data Augmentation Transfer Learning

TRECVID 2019: An Evaluation Campaign to Benchmark Video Activity Detection, Video Captioning and Matching, and Video Search & Retrieval

no code implementations21 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.

Action Detection Activity Detection +5

Tracking Skin Colour and Wrinkle Changes During Cosmetic Product Trials Using Smartphone Images

no code implementations4 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.

Utilising Visual Attention Cues for Vehicle Detection and Tracking

no code implementations31 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.

Object object-detection +2

A Neuro-AI Interface for Evaluating Generative Adversarial Networks

1 code implementation5 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.

Speech Synthesis

End-to-End Conditional GAN-based Architectures for Image Colourisation

1 code implementation26 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.

A Neuro-AI Interface: Learning DNNs from the Human Brain

no code implementations28 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.

Object Recognition Open-Ended Question Answering

Synthetic-Neuroscore: Using A Neuro-AI Interface for Evaluating Generative Adversarial Networks

1 code implementation10 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.

Image Generation Speech Synthesis

Spatial Filtering Pipeline Evaluation of Cortically Coupled Computer Vision System for Rapid Serial Visual Presentation

no code implementations15 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).

EEG General Classification +2

Use of Neural Signals to Evaluate the Quality of Generative Adversarial Network Performance in Facial Image Generation

no code implementations10 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.

Brain Computer Interface Generative Adversarial Network +1

Exploring EEG for Object Detection and Retrieval

no code implementations9 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.

Content-Based Image Retrieval EEG +4

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