Zobrazeno 1 - 10
of 2 305
pro vyhledávání: '"McGuinness, Kevin"'
Autor:
Albert, Paul, Valmadre, Jack, Arazo, Eric, Krishna, Tarun, O'Connor, Noel E., McGuinness, Kevin
Training a classifier on web-crawled data demands learning algorithms that are robust to annotation errors and irrelevant examples. This paper builds upon the recent empirical observation that applying unsupervised contrastive learning to noisy, web-
Externí odkaz:
http://arxiv.org/abs/2407.05528
Autor:
Wang, Qiang, Deng, Yixin, Sanchez, Francisco Roldan, Wang, Keru, McGuinness, Kevin, O'Connor, Noel, Redmond, Stephen J.
Offline policy learning aims to discover decision-making policies from previously-collected datasets without additional online interactions with the environment. As the training dataset is fixed, its quality becomes a crucial determining factor in th
Externí odkaz:
http://arxiv.org/abs/2402.09550
Autor:
Rai, Ayush K., Krishna, Tarun, Hu, Feiyan, Drimbarean, Alexandru, McGuinness, Kevin, Smeaton, Alan F., O'Connor, Noel E.
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 anomalou
Externí odkaz:
http://arxiv.org/abs/2311.16514
Autor:
Sanchez, Francisco Roldan, Wang, Qiang, Bulens, David Cordova, McGuinness, Kevin, Redmond, Stephen, O'Connor, Noel
Hindsight Experience Replay (HER) is a technique used in reinforcement learning (RL) that has proven to be very efficient for training off-policy RL-based agents to solve goal-based robotic manipulation tasks using sparse rewards. Even though HER imp
Externí odkaz:
http://arxiv.org/abs/2310.01827
Early detection of colorectal polyps is of utmost importance for their treatment and for colorectal cancer prevention. Computer vision techniques have the potential to aid professionals in the diagnosis stage, where colonoscopies are manually carried
Externí odkaz:
http://arxiv.org/abs/2307.12033
Autor:
Maniparambil, Mayug, Vorster, Chris, Molloy, Derek, Murphy, Noel, McGuinness, Kevin, O'Connor, Noel E.
Contrastive pretrained large Vision-Language Models (VLMs) like CLIP have revolutionized visual representation learning by providing good performance on downstream datasets. VLMs are 0-shot adapted to a downstream dataset by designing prompts that ar
Externí odkaz:
http://arxiv.org/abs/2307.11661
Deep learning has shown excellent performance in analysing medical images. However, datasets are difficult to obtain due privacy issues, standardization problems, and lack of annotations. We address these problems by producing realistic synthetic ima
Externí odkaz:
http://arxiv.org/abs/2307.11253
Chest X-rays have been widely used for COVID-19 screening; however, 3D computed tomography (CT) is a more effective modality. We present our findings on COVID-19 severity prediction from chest CT scans using the STOIC dataset. We developed an ensembl
Externí odkaz:
http://arxiv.org/abs/2305.10115
Autor:
Brennan, Conor, McGuinness, Kevin
This paper describes deep learning models based on convolutional neural networks applied to the problem of predicting EM wave propagation over rural terrain. A surface integral equation formulation, solved with the method of moments and accelerated u
Externí odkaz:
http://arxiv.org/abs/2302.01052
Autor:
Wang, Qiang, McCarthy, Robert, Bulens, David Cordova, Sanchez, Francisco Roldan, McGuinness, Kevin, O'Connor, Noel E., Redmond, Stephen J.
This paper presents our solution for the Real Robot Challenge (RRC) III, a competition featured in the NeurIPS 2022 Competition Track, aimed at addressing dexterous robotic manipulation tasks through learning from pre-collected offline data. Particip
Externí odkaz:
http://arxiv.org/abs/2301.13019