334 citations · 1.2k across the 64 of their papers we have counts for
17 papers · 1 filter
Hierarchical reinforcement learning for in-hand robotic manipulation using Davenport chained rotations
Francisco Roldan Sanchez, Qiang Wang, David Cordova Bulens +3
End-to-end reinforcement learning techniques are among the most successful methods for robotic manipulation tasks. However, the training time required to find a good policy capable…
Is your noise correction noisy? PLS: Robustness to label noise with two stage detection
Paul Albert, Eric Arazo, Tarun Krishna +2
Designing robust algorithms capable of training accurate neural networks on uncurated datasets from the web has been the subject of much research as it reduces the need for time co…
Motion Aware Self-Supervision for Generic Event Boundary Detection
Ayush K. Rai, Tarun Krishna, Julia Dietlmeier +3
The task of Generic Event Boundary Detection (GEBD) aims to detect moments in videos that are naturally perceived by humans as generic and taxonomy-free event boundaries. Modeling…
BaseTransformers: Attention over base data-points for One Shot Learning
Mayug Maniparambil, Kevin McGuinness, Noel O'Connor
Few shot classification aims to learn to recognize novel categories using only limited samples per category. Most current few shot methods use a base dataset rich in labeled exampl…
Random Data Augmentation based Enhancement: A Generalized Enhancement Approach for Medical Datasets
Sidra Aleem, Teerath Kumar, Suzanne Little +3
Over the years, the paradigm of medical image analysis has shifted from manual expertise to automated systems, often using deep learning (DL) systems. The performance of deep learn…
Fast and Robust Video-Based Exercise Classification via Body Pose Tracking and Scalable Multivariate Time Series Classifiers
Ashish Singh, Antonio Bevilacqua, Thach Le Nguyen +6
Technological advancements have spurred the usage of machine learning based applications in sports science. Physiotherapists, sports coaches and athletes actively look to incorpora…
Towards advanced robotic manipulation
Francisco Roldan Sanchez, Stephen Redmond, Kevin McGuinness +1
Robotic manipulation and control has increased in importance in recent years. However, state of the art techniques still have limitations when required to operate in real world app…
Cardiac Segmentation using Transfer Learning under Respiratory Motion Artifacts
Carles Garcia-Cabrera, Eric Arazo, Kathleen M. Curran +2
Methods that are resilient to artifacts in the cardiac magnetic resonance imaging (MRI) while performing ventricle segmentation, are crucial for ensuring quality in structural and…
Embedding contrastive unsupervised features to cluster in- and out-of-distribution noise in corrupted image datasets
Paul Albert, Eric Arazo, Noel E. O'Connor +1
Using search engines for web image retrieval is a tempting alternative to manual curation when creating an image dataset, but their main drawback remains the proportion of incorrec…
Dynamic Channel Selection in Self-Supervised Learning
Tarun Krishna, Ayush K. Rai, Yasser A. D. Djilali +3
Whilst computer vision models built using self-supervised approaches are now commonplace, some important questions remain. Do self-supervised models learn highly redundant channel…
Segmentation Enhanced Lameness Detection in Dairy Cows from RGB and Depth Video
Eric Arazo, Robin Aly, Kevin McGuinness
Cow lameness is a severe condition that affects the life cycle and life quality of dairy cows and results in considerable economic losses. Early lameness detection helps farmers ad…
Dexterous Robotic Manipulation using Deep Reinforcement Learning and Knowledge Transfer for Complex Sparse Reward-based Tasks
Qiang Wang, Francisco Roldan Sanchez, Robert McCarthy +7
This paper describes a deep reinforcement learning (DRL) approach that won Phase 1 of the Real Robot Challenge (RRC) 2021, and then extends this method to a more difficult manipula…
Utilizing unsupervised learning to improve sward content prediction and herbage mass estimation
Paul Albert, Mohamed Saadeldin, Badri Narayanan +5
Sward species composition estimation is a tedious one. Herbage must be collected in the field, manually separated into components, dried and weighed to estimate species composition…
Unsupervised domain adaptation and super resolution on drone images for autonomous dry herbage biomass estimation
Paul Albert, Mohamed Saadeldin, Badri Narayanan +5
Herbage mass yield and composition estimation is an important tool for dairy farmers to ensure an adequate supply of high quality herbage for grazing and subsequently milk producti…
Synthetic data for unsupervised polyp segmentation
Enric Moreu, Kevin McGuinness, Noel E. O'Connor
Deep learning has shown excellent performance in analysing medical images. However, datasets are difficult to obtain due privacy issues, standardization problems, and lack of annot…
Domain Randomization for Object Counting
Enric Moreu, Kevin McGuinness, Diego Ortego +1
Recently, the use of synthetic datasets based on game engines has been shown to improve the performance of several tasks in computer vision. However, these datasets are typically o…
BERTHA: Video Captioning Evaluation Via Transfer-Learned Human Assessment
Luis Lebron, Yvette Graham, Kevin McGuinness +2
Evaluating video captioning systems is a challenging task as there are multiple factors to consider; for instance: the fluency of the caption, multiple actions happening in a singl…