Zobrazeno 1 - 10
of 14
pro vyhledávání: '"Chaitanya Kaul"'
Autor:
Chaitanya Kaul, Kevin J. Mitchell, Khaled Kassem, Athanasios Tragakis, Valentin Kapitany, Ilya Starshynov, Federica Villa, Roderick Murray-Smith, Daniele Faccio
Publikováno v:
Sensors, Vol 24, Iss 18, p 5865 (2024)
In the field of detection and ranging, multiple complementary sensing modalities may be used to enrich information obtained from a dynamic scene. One application of this sensor fusion is in public security and surveillance, where efficacy and privacy
Externí odkaz:
https://doaj.org/article/de5622e7f022420f89ddbd247b212882
Autor:
James K. Ruffle, Robert J Gray, Samia Mohinta, Guilherme Pombo, Chaitanya Kaul, Harpreet Hyare, Geraint Rees, Parashkev Nachev
Publikováno v:
NeuroImage, Vol 291, Iss , Pp 120600- (2024)
Our knowledge of the organisation of the human brain at the population-level is yet to translate into power to predict functional differences at the individual-level, limiting clinical applications and casting doubt on the generalisability of inferre
Externí odkaz:
https://doaj.org/article/bffad76a626b4c6897c835435a69cb38
Autor:
Marija Jegorova, Chaitanya Kaul, Charlie Mayor, Alison Q. O'Neil, Alexander Weir, Roderick Murray-Smith, Sotirios A. Tsaftaris
Publikováno v:
IEEE Transactions on Pattern Analysis and Machine Intelligence. :1-20
Leakage of data from publicly available Machine Learning (ML) models is an area of growing significance as commercial and government applications of ML can draw on multiple sources of data, potentially including users' and clients' sensitive data. We
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f075ced43c962dccd937aae368ce62e0
https://doi.org/10.1109/tpami.2022.3229593
https://doi.org/10.1109/tpami.2022.3229593
Publikováno v:
Computer Vision – ACCV 2022 Workshops ISBN: 9783031270659
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6b1bf31ba1f19805a626a38a8878785c
https://doi.org/10.1007/978-3-031-27066-6_22
https://doi.org/10.1007/978-3-031-27066-6_22
Autor:
Qianying Liu, Chaitanya Kaul, Jun Wang, Christos Anagnostopoulos, Roderick Murray-Smith, Fani Deligianni
For medical image semantic segmentation (MISS), Vision Transformers have emerged as strong alternatives to convolutional neural networks thanks to their inherent ability to capture long-range correlations. However, existing research uses off-the-shel
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::12b56d651813ee59d189b44dffdcf119
We propose a novel transformer model, capable of segmenting medical images of varying modalities. Challenges posed by the fine grained nature of medical image analysis mean that the adaptation of the transformer for their analysis is still at nascent
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::819c9024a0c72de5420c9636dc58f6aa
Autor:
Chaitanya Kaul, Neeraj Sharma
Publikováno v:
2021 International Conference on Computational Performance Evaluation (ComPE).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::13de2393b8a4333665de9386b60d55e3
https://doi.org/10.1109/compe53109.2021.9752254
https://doi.org/10.1109/compe53109.2021.9752254
Publikováno v:
ICPR
The application of deep learning to 3D point clouds is challenging due to its lack of order. Inspired by the point embeddings of PointNet and the edge embeddings of DGCNNs, we propose three improvements to the task of point cloud analysis. First, we
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::27b95cbc21bf035ee1c32f92a1e10613
http://arxiv.org/abs/2104.03427
http://arxiv.org/abs/2104.03427
Publikováno v:
Pattern Recognition. ICPR International Workshops and Challenges ISBN: 9783030687625
ICPR Workshops (1)
ICPR Workshops (1)
Loss functions are error metrics that quantify the difference between a prediction and its corresponding ground truth. Fundamentally, they define a functional landscape for traversal by gradient descent. Although numerous loss functions have been pro
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::fcc8dfebbfe1c69415edc79ad4abc0a4
https://doi.org/10.1007/978-3-030-68763-2_28
https://doi.org/10.1007/978-3-030-68763-2_28
Publikováno v:
Artificial intelligence in medicine. 117
Weaning from mechanical ventilation covers the process of liberating the patient from mechanical support and removing the associated endotracheal tube. The management of weaning from mechanical ventilation comprises a significant proportion of the ca
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b1f068d0a4e8f72462fb708ded02e00c
https://pubmed.ncbi.nlm.nih.gov/34127233
https://pubmed.ncbi.nlm.nih.gov/34127233