Zobrazeno 1 - 10
of 440
pro vyhledávání: '"P. Sudheendra"'
We propose a novel approach to assess the public's coping behavior during the COVID-19 outbreak by examining the emotions. Specifically, we explore (1) changes in the public's emotions with the COVID-19 crisis progression and (2) the impacts of the p
Externí odkaz:
http://arxiv.org/abs/2409.10754
Origami structures have been receiving a lot of attention from engineering and scientific researchers owing to their unique properties such as deployability, multi-stability, negative stiffness, etc. However, dynamic properties of origami structures
Externí odkaz:
http://arxiv.org/abs/2408.01889
Autor:
Lauren D. Otto-Dobos, Lindsay D. Strehle, Brett R. Loman, Melina M. Seng, Sagar D. Sardesai, Nicole O. Williams, Margaret E. Gatti-Mays, Daniel G. Stover, Preeti K. Sudheendra, Robert Wesolowski, Rebecca R. Andridge, Michael T. Bailey, Leah M. Pyter
Publikováno v:
npj Breast Cancer, Vol 10, Iss 1, Pp 1-12 (2024)
Abstract Chemotherapy frequently causes debilitating gastrointestinal symptoms, which are inadequately managed by current treatments. Recent research indicates the gut microbiome plays a role in the pathogenesis of these symptoms. The current study a
Externí odkaz:
https://doaj.org/article/04e252979f9f4ccdb88f619c16922f89
If you ask a human to describe an image, they might do so in a thousand different ways. Traditionally, image captioning models are trained to generate a single "best" (most like a reference) image caption. Unfortunately, doing so encourages captions
Externí odkaz:
http://arxiv.org/abs/2302.01328
Autor:
Rathod, Vivek, Seybold, Bryan, Vijayanarasimhan, Sudheendra, Myers, Austin, Gu, Xiuye, Birodkar, Vighnesh, Ross, David A.
Detecting actions in untrimmed videos should not be limited to a small, closed set of classes. We present a simple, yet effective strategy for open-vocabulary temporal action detection utilizing pretrained image-text co-embeddings. Despite being trai
Externí odkaz:
http://arxiv.org/abs/2212.10596
Autor:
Kai C. C. Johnson, Ai Ni, Dionisia Quiroga, Ashley C. Pariser, Preeti K. Sudheendra, Nicole O. Williams, Sagar D. Sardesai, Mathew Cherian, Daniel G. Stover, Margaret Gatti-Mays, Bhuvaneswari Ramaswamy, Maryam Lustberg, Sachin Jhawar, Roman Skoracki, Robert Wesolowski
Publikováno v:
npj Breast Cancer, Vol 10, Iss 1, Pp 1-8 (2024)
Abstract There is limited data regarding the added benefit of adjuvant systemic therapy in the management of small, node-negative, HER2+ breast cancer. In a multi-institutional retrospective analysis using the American Society of Clinical Oncology Ca
Externí odkaz:
https://doaj.org/article/fc9fb37c438d44728b8717088153f8ae
Autor:
Chan, David M, Ni, Yiming, Ross, David A, Vijayanarasimhan, Sudheendra, Myers, Austin, Canny, John
Traditional automated metrics for evaluating conditional natural language generation use pairwise comparisons between a single generated text and the best-matching gold-standard ground truth text. When multiple ground truths are available, scores are
Externí odkaz:
http://arxiv.org/abs/2209.07518
Autor:
Chan, David M., Myers, Austin, Vijayanarasimhan, Sudheendra, Ross, David A., Seybold, Bryan, Canny, John F.
While there have been significant gains in the field of automated video description, the generalization performance of automated description models to novel domains remains a major barrier to using these systems in the real world. Most visual descrip
Externí odkaz:
http://arxiv.org/abs/2205.06253
Autor:
Jasmine S. Sukumar, Sagar Sardesai, Andy Ni, Nicole Williams, Kai Johnson, Dionisia Quiroga, Bhuvana Ramaswamy, Robert Wesolowski, Mathew Cherian, Daniel G. Stover, Margaret Gatti‐Mays, Ashley Pariser, Preeti Sudheendra, Mridula A. George, Maryam Lustberg
Publikováno v:
Cancer Medicine, Vol 13, Iss 12, Pp n/a-n/a (2024)
Abstract Background The optimal adjuvant endocrine therapy (ET) in hormone receptor positive (HR+) and human epidermal growth factor receptor 2 positive (HER2+) premenopausal breast cancer (BC) remains unclear. Moreover, the benefit and clinical indi
Externí odkaz:
https://doaj.org/article/95ee2addb7d44134809b3c59d72db720
Automatic video captioning aims to train models to generate text descriptions for all segments in a video, however, the most effective approaches require large amounts of manual annotation which is slow and expensive. Active learning is a promising w
Externí odkaz:
http://arxiv.org/abs/2007.13913