Zobrazeno 1 - 10
of 254
pro vyhledávání: '"DILIP K. PRASAD"'
Autor:
Deepak K. Gupta, Udbhav Bamba, Abhishek Thakur, Akash Gupta, Rohit Agarwal, Suraj Sharan, Ertugul Demir, Krishna Agarwal, Dilip K. Prasad
Publikováno v:
Scientific Data, Vol 11, Iss 1, Pp 1-14 (2024)
Abstract Current convolutional neural networks (CNNs) are not designed for large scientific images with rich multi-scale features, such as in satellite and microscopy domain. A new phase of development of CNNs especially designed for large images is
Externí odkaz:
https://doaj.org/article/a1de9fdffb7c4a46a59febb016ea877d
Publikováno v:
Applied Sciences, Vol 14, Iss 22, p 10677 (2024)
Global contexts in images are quite valuable in image-to-image translation problems. Conventional attention-based and graph-based models capture the global context to a large extent; however, these are computationally expensive. Moreover, existing ap
Externí odkaz:
https://doaj.org/article/fc74c422da5f40788588f3df58acbe54
Publikováno v:
Transportation Research Interdisciplinary Perspectives, Vol 24, Iss , Pp 101047- (2024)
Maritime training can improve safety by equipping seafarers with the knowledge and skills to manage risk. However, designing a quality training program can be challenging and stress can negatively impact performance and safety. To address this, the p
Externí odkaz:
https://doaj.org/article/54b0a2c26b6c4ba1bff91f9d2fbf6390
Autor:
Pragyan Banerjee, Shivam Milind Akarte, Prakhar Kumar, Muhammad Shamsuzzaman, Ankit Butola, Krishna Agarwal, Dilip K Prasad, Frank Melandsø, Anowarul Habib
Publikováno v:
Machine Learning: Science and Technology, Vol 5, Iss 1, p 015007 (2024)
Acoustic microscopy is a cutting-edge label-free imaging technology that allows us to see the surface and interior structure of industrial and biological materials. The acoustic image is created by focusing high-frequency acoustic waves on the object
Externí odkaz:
https://doaj.org/article/b39723971bc04d8d9f8d369eeb03b91e
Autor:
Pragyan Banerjee, Sibasish Mishra, Nitin Yadav, Krishna Agarwal, Frank Melandsø, Dilip K. Prasad, Anowarul Habib
Publikováno v:
AIP Advances, Vol 13, Iss 4, Pp 045225-045225-12 (2023)
Scanning acoustic microscopy (SAM) is a non-ionizing and label-free imaging modality used to visualize the surface and internal structures of industrial objects and biological specimens. The image of the sample under investigation is created using hi
Externí odkaz:
https://doaj.org/article/4d2551d065904ad98b0a6d20b5b53e8a
Publikováno v:
AI, Vol 3, Iss 1, Pp 124-145 (2022)
Federated learning promises an elegant solution for learning global models across distributed and privacy-protected datasets. However, challenges related to skewed data distribution, limited computational and communication resources, data poisoning,
Externí odkaz:
https://doaj.org/article/81f515a55b024b7bbc9b144c3e28e84e
Publikováno v:
IEEE/ASME Transactions on Mechatronics. 28:302-313
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::55f114ffa628fce63184f1408e6c2ee9
https://doi.org/10.1109/tmech.2022.3193895
https://doi.org/10.1109/tmech.2022.3193895
Publikováno v:
Applied Sciences, Vol 11, Iss 20, p 9765 (2021)
This work presents a novel approach to detecting stress differences between experts and novices in Situation Awareness (SA) tasks during maritime navigation using one type of wearable sensor, Empatica E4 Wristband. We propose that for a given workloa
Externí odkaz:
https://doaj.org/article/447a9a8246604c0ba1b4d423ace3f0c2
Autor:
Krishna Agarwal, Dilip K. Prasad
Publikováno v:
Scientific Reports, Vol 7, Iss 1, Pp 1-10 (2017)
Abstract This paper presents eigen-analysis of image stack of blinking fluorophores to identify the components that enable super-resolved imaging of blinking fluorophores. Eigen-analysis reveals that the contributions of spatial distribution of fluor
Externí odkaz:
https://doaj.org/article/c286e9297b334b2fa5e25aa17ff1af7c
Publikováno v:
Interpretability in Deep Learning ISBN: 9783031206382
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::491d0799439a90e7a233cc1c02065ecf
https://doi.org/10.1007/978-3-031-20639-9_2
https://doi.org/10.1007/978-3-031-20639-9_2
