Zobrazeno 1 - 10
of 5 655
pro vyhledávání: '"Puranam P"'
Publikováno v:
International Journal of Tamil Language and Literary Studies, Vol 5, Iss 1, Pp 25-37 (2022)
‘Puzhavar Puranam’ is a book written by Dantapani Swami who lived in the 19th century. The ideas expressed in it emphasize equality between the six Vedic Religions. It is also seen as an attempt of religious integration. Some stories in ‘Puzhav
Externí odkaz:
https://doaj.org/article/0eaa3380a4514e9aacd8b6775d8280f9
Pattern recognition-based myoelectric control is traditionally trained with static or ramp contractions, but this fails to capture the dynamic nature of real-world movements. This study investigated the benefits of training classifiers with continuou
Externí odkaz:
http://arxiv.org/abs/2409.16015
Publikováno v:
Biomedical Signal Processing and Control, vol. 71, p. 103134, Jan. 2022
Despite continued efforts to improve classification accuracy, it has been reported that offline accuracy is a poor indicator of the usability of pattern recognition-based myoelectric control. One potential source of this disparity is the existence of
Externí odkaz:
http://arxiv.org/abs/2409.14172
Publikováno v:
S. T. P. Raghu, D. MacIsaac and E. Scheme, IEEE Journal of Biomedical and Health Informatics, vol. 27, no. 12, pp. 6051-6061, Dec. 2023
Post-processing techniques have been shown to improve the quality of the decision stream generated by classifiers used in pattern-recognition-based myoelectric control. However, these techniques have largely been tested individually and on well-behav
Externí odkaz:
http://arxiv.org/abs/2409.14169
In this study, we investigate the application of self-supervised learning via pre-trained Long Short-Term Memory (LSTM) networks for training surface electromyography pattern recognition models (sEMG-PR) using dynamic data with transitions. While lab
Externí odkaz:
http://arxiv.org/abs/2409.11632
Autor:
Phogat, Karmvir Singh, Puranam, Sai Akhil, Dasaratha, Sridhar, Harsha, Chetan, Ramakrishna, Shashishekar
Recent research has shown that smaller language models can acquire substantial reasoning abilities when fine-tuned with reasoning exemplars crafted by a significantly larger teacher model. We explore this paradigm for the financial domain, focusing o
Externí odkaz:
http://arxiv.org/abs/2408.12337
Autor:
Tam, Simon, Raghu, Shriram Tallam Puranam, Buteau, Étienne, Scheme, Erik, Boukadoum, Mounir, Campeau-Lecours, Alexandre, Gosselin, Benoit
Current electromyography (EMG) pattern recognition (PR) models have been shown to generalize poorly in unconstrained environments, setting back their adoption in applications such as hand gesture control. This problem is often due to limited training
Externí odkaz:
http://arxiv.org/abs/2404.15360
Publikováno v:
Intelligent Medicine, Vol 4, Iss 3, Pp 161-169 (2024)
Objective: Segmentation of medical images is a crucial process in various image analysis applications. Automated segmentation methods excel in accuracy when compared to manual segmentation in the context of medical image analysis. One of the essentia
Externí odkaz:
https://doaj.org/article/39d3656af2af42738d78b0a596b72c9e
Autor:
Özgecan Koçak, Phanish Puranam
Publikováno v:
Sociologica, Vol 18, Iss 1, Pp 117-137 (2024)
Misunderstandings often lead to accidents, delays, missed opportunities, waste, and conflict in organizations. However, on occasion, they can also lead to beneficial outcomes, at least for one of the parties involved. Prior scholarship on productive
Externí odkaz:
https://doaj.org/article/16d44dcb943f4dada6d6da5eeb2e404f
Autor:
Tommaso Simoncini, Hisham Arab, Nataliia Pedachenko, Qinjie Tian, Fernando Pineda, Balamba Puranam, Rubina Sohail, Maria Celeste Osorio Wender
Publikováno v:
Gynecological Endocrinology, Vol 40, Iss 1 (2024)
Ovulatory disorders are a common cause of abnormal uterine bleeding in women of reproductive age. The International Federation of Gynecology and Obstetrics currently offers a causal classification system for ovulatory disorders but does not provide c
Externí odkaz:
https://doaj.org/article/4324abeee5624a3b8ebf0576d7db95ae