Zobrazeno 1 - 10
of 13
pro vyhledávání: '"Kowshik Thopalli"'
Publikováno v:
IEEE Access, Vol 11, Pp 108356-108364 (2023)
Recent advancements in developing pre-trained models using large-scale datasets have emphasized the importance of robust protocols to adapt them effectively to domain-specific data, especially when the available data is limited. To achieve data-effic
Externí odkaz:
https://doaj.org/article/e56af13db69242bf9b4d9585cf28ac01
Publikováno v:
IEEE Access, Vol 11, Pp 12858-12869 (2023)
Unsupervised domain adaptation (UDA) aims to transfer and adapt knowledge from a labeled source domain to an unlabeled target domain. Traditionally, geometry-based alignment methods, e.g., Orthogonal Procrustes Alignment (OPA), formed an important cl
Externí odkaz:
https://doaj.org/article/96e4297483e44cfd8cf4c35d8114dd3e
Publikováno v:
Scientific Reports, Vol 12, Iss 1, Pp 1-15 (2022)
Abstract The rapid adoption of artificial intelligence methods in healthcare is coupled with the critical need for techniques to rigorously introspect models and thereby ensure that they behave reliably. This has led to the design of explainable AI t
Externí odkaz:
https://doaj.org/article/4b559289c0894052b52c6f8552335505
Autor:
Tamim Ahmed, Kowshik Thopalli, Thanassis Rikakis, Pavan Turaga, Aisling Kelliher, Jia-Bin Huang, Steven L. Wolf
Publikováno v:
Frontiers in Neurology, Vol 12 (2021)
We are developing a system for long term Semi-Automated Rehabilitation At the Home (SARAH) that relies on low-cost and unobtrusive video-based sensing. We present a cyber-human methodology used by the SARAH system for automated assessment of upper ex
Externí odkaz:
https://doaj.org/article/8e5a60f6bbeb4031a7dd650692c37af3
Autor:
Rakshith Subramanyam, Kowshik Thopalli, Spring Berman, Pavan Turaga, Jayaraman J. Thiagarajan
Publikováno v:
ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).
Publikováno v:
Scientific Reports, Vol 12, Iss 1, Pp 1-15 (2022)
Scientific Reports
Scientific Reports
Artificial intelligence methods such as deep neural networks promise unprecedented capabilities in healthcare, from diagnosing diseases to prescribing treatments. While this can eventually produce a valuable suite of tools for automating clinical wor
Publikováno v:
International Journal of Pattern Recognition and Artificial Intelligence. 36
Improving the reliability of nighttime pedestrian detection is a crucial challenge towards the design of robust autonomous systems. Not surprisingly, most pedestrian fatalities occur in low-illumination settings, thus emphasizing the need for new alg
Autor:
Tamim Ahmed, Thanassis Rikakis, Setor Zilevu, Aisling Kelliher, Kowshik Thopalli, Pavan Turaga, Steven L. Wolf
BackgroundThe evidence-based quantification of the relation between changes in movement quality and functionality can assist clinicians in achieving more effective structuring or adaptations of therapy. Facilitating this quantification through comput
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1e13ef57d0f9f828b009406c58219ab8
https://doi.org/10.1101/2022.05.25.22275480
https://doi.org/10.1101/2022.05.25.22275480
Autor:
Pavan Turaga, Kowshik Thopalli, Tamim Ahmed, Thanassis Rikakis, Aisling Kelliher, Steven L. Wolf, Jia-Bin Huang
Publikováno v:
Frontiers in Neurology
Frontiers in Neurology, Vol 12 (2021)
Frontiers in Neurology, Vol 12 (2021)
We are developing a system for long term Semi-Automated Rehabilitation At the Home (SARAH) that relies on low-cost and unobtrusive video-based sensing. We present a cyber-human methodology used by the SARAH system for automated assessment of upper ex
Autor:
Kowshik Thopalli, Zachary Seymour, Supun Samarasekera, Han-Pang Chiu, Rakesh Kumar, Niluthpol Chowdhury Mithun
Publikováno v:
ICRA
Visual navigation for autonomous agents is a core task in the fields of computer vision and robotics. Learning-based methods, such as deep reinforcement learning, have the potential to outperform the classical solutions developed for this task; howev