Zobrazeno 1 - 10
of 1 836
pro vyhledávání: '"P. Gowtham"'
Publikováno v:
Heliyon, Vol 10, Iss 13, Pp e34022- (2024)
The communication network made the globe a single entity and easily acessible by everyone at any time. Growth in communication networks is unimaginable and advanced nowadays. It is growing every day by means of medium or components used in communicat
Externí odkaz:
https://doaj.org/article/688668c5cabf4b1b9451551e00104e03
Publikováno v:
Songklanakarin Journal of Science and Technology (SJST), Vol 44, Iss 6, Pp 1407-1411 (2022)
Shape Memory Alloys (SMAs) offer specific adaptability to complex shaped structural parts. In this study, two dissimilar shape memory alloys are welded by friction welding and put through mechanical testing to find the best results for those alloys
Externí odkaz:
https://doaj.org/article/3841fd777ce74ce6985b10a9e72513a1
Speech-based assessment of the schizophrenia spectrum has been widely researched over in the recent past. In this study, we develop a deep learning framework to estimate schizophrenia severity scores from speech using a feature fusion approach that f
Externí odkaz:
http://arxiv.org/abs/2411.06033
Autor:
Saha, Saheli, Banerjee, Debasmita, Ram, Rishi, Reddy, Gowtham, Guha, Debashree, Sarkar, Arnab, Dutta, Bapi, S, Moses ArunSingh, Chakraborty, Suman, Mallick, Indranil
Dose prediction is an area of ongoing research that facilitates radiotherapy planning. Most commercial models utilise imaging data and intense computing resources. This study aimed to predict the dose-volume of rectum and bladder from volumes of targ
Externí odkaz:
http://arxiv.org/abs/2411.05378
Autor:
Bukas, Christina, Subramanian, Harshavardhan, See, Fenja, Steinchen, Carina, Ezhov, Ivan, Boosarpu, Gowtham, Asgharpour, Sara, Burgstaller, Gerald, Lehmann, Mareike, Kofler, Florian, Piraud, Marie
High-throughput image analysis in the biomedical domain has gained significant attention in recent years, driving advancements in drug discovery, disease prediction, and personalized medicine. Organoids, specifically, are an active area of research,
Externí odkaz:
http://arxiv.org/abs/2410.14612
Autor:
Murugesan, Gowtham Krishnan, McCrumb, Diana, Soni, Rahul, Kumar, Jithendra, Nuernberg, Leonard, Pei, Linmin, Wagner, Ulrike, Granger, Sutton, Fedorov, Andrey Y., Moore, Stephen, Van Oss, Jeff
AI in Medical Imaging project aims to enhance the National Cancer Institute's (NCI) Image Data Commons (IDC) by developing nnU-Net models and providing AI-assisted segmentations for cancer radiology images. We created high-quality, AI-annotated imagi
Externí odkaz:
http://arxiv.org/abs/2409.20342
Detecting and measuring confounding effects from data is a key challenge in causal inference. Existing methods frequently assume causal sufficiency, disregarding the presence of unobserved confounding variables. Causal sufficiency is both unrealistic
Externí odkaz:
http://arxiv.org/abs/2409.17840
Multimodal schizophrenia assessment systems have gained traction over the last few years. This work introduces a schizophrenia assessment system to discern between prominent symptom classes of schizophrenia and predict an overall schizophrenia severi
Externí odkaz:
http://arxiv.org/abs/2409.09733
Black hole perturbation theory on spherically symmetric backgrounds has been instrumental in establishing various aspects about the gravitational dynamics close to black holes, and continues to be an interesting avenue to confront current challenges
Externí odkaz:
http://arxiv.org/abs/2408.13557
Autor:
Vashishtha, Aniket, Kumar, Abhinav, Reddy, Abbavaram Gowtham, Balasubramanian, Vineeth N, Sharma, Amit
For text-based AI systems to interact in the real world, causal reasoning is an essential skill. Since interventional data is costly to generate, we study to what extent an agent can learn causal reasoning from passive data. Specifically, we consider
Externí odkaz:
http://arxiv.org/abs/2407.07612