Zobrazeno 1 - 6
of 6
pro vyhledávání: '"Bipin Gaikwad"'
Autor:
Abhijit Karmakar, Bipin Gaikwad
Publikováno v:
Journal of Real-Time Image Processing. 18:1993-2007
In this work, we have presented an end-to-end multi-person multi-camera tracking (MPMCT) surveillance system and implemented it on edge analytics platform for real-time performance. The proposed MPMCT framework is both privacy-aware and scalable supp
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::487bd62e7b283dd98044f3f05fa40ce8
https://doi.org/10.1007/s11554-020-01066-8
https://doi.org/10.1007/s11554-020-01066-8
Prediction of threshold voltage of GaN HEMTs using deep learning model designed by genetic algorithm
Publikováno v:
Materials Science in Semiconductor Processing. 152:107057
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::263d14e4e68fe6416f9b31255fd00a93
https://doi.org/10.1016/j.mssp.2022.107057
https://doi.org/10.1016/j.mssp.2022.107057
Publikováno v:
ICCCNT
In this work, we have proposed a state-of-the-art face logging system that detects and logs high quality cropped face images of the people in real-time for security applications. Multiple strategies based on resolution, velocity and symmetry of faces
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::10ff8efc70806532081980e5c06a18b6
https://doi.org/10.1109/icccnt51525.2021.9579758
https://doi.org/10.1109/icccnt51525.2021.9579758
Publikováno v:
Journal of Applied Physics. 132:044902
This research article proposes a deep learning framework that addresses two major hurdles in adopting deep learning techniques for solving physics-based problems. One is the requirement of a large data set for training the deep learning (DL) model an
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ef861553dd0a33c00ac466c59e815498
https://doi.org/10.1063/5.0087344
https://doi.org/10.1063/5.0087344
Autor:
Bipin Gaikwad, Abhijit Karmakar
Publikováno v:
Computers and Electrical Engineering. 99:107824
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8d24466509a36855d4411c61c4650259
https://doi.org/10.1016/j.compeleceng.2022.107824
https://doi.org/10.1016/j.compeleceng.2022.107824