Zobrazeno 1 - 6
of 6
pro vyhledávání: '"Ashok Vishnoi"'
Autor:
Gaurav Govardhan, Rupal Ambulkar, Santosh Kulkarni, Ashok Vishnoi, Prafull Yadav, Begum Abida Choudhury, Manoj Khare, Sachin D. Ghude
Publikováno v:
Heliyon, Vol 9, Iss 6, Pp e16939- (2023)
Stubble-burning in northern India is an important source of atmospheric particulate matter (PM) and trace gases, which significantly impact local and regional climate, in addition to causing severe health risks. Scientific research on assessing the i
Externí odkaz:
https://doaj.org/article/02a2e77642f644939c113cd5b1fc31cb
Autor:
Gaurav Govardhan, Rupal Ambulkar, Santosh Kulkarni, Ashok Vishnoi, Praful Yadav, B. Abida Choudhury, Manoj Khare, Sachin D. Ghude
Stubble-burning in northern India is an important source of atmospheric particulate matter (PM) and trace gases, which significantly impact local and regional climate, in addition to causing severe health risks. Scientific research on assessing the i
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::258f9136bdf21249a9d364e2af8d7743
https://doi.org/10.21203/rs.3.rs-1406844/v1
https://doi.org/10.21203/rs.3.rs-1406844/v1
Autor:
Sirish Kumar Pasupuleti, Raj Narayana Gadde, R Chandra Kumar, Vasanthakumar Rajagopal, Ashok Vishnoi, Narasinga Rao Miniskar, N Chandra Sekhar
Publikováno v:
ISCAS
Recurrent Neural Networks (RNN) have demonstrated excellent results for various Automatic Speech Recognition (ASR) and Natural Language Processing (NLP) tasks. However, executing RNNs requires huge memory and computations which makes it difficult to
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::68b20a879223f6fc180e3602cef3c92e
https://doi.org/10.1109/iscas.2019.8702528
https://doi.org/10.1109/iscas.2019.8702528
Autor:
Chandra Kumar Ramasamy, Ashok Vishnoi, Sirish Kumar Pasupuleti, Vasanthakumar Rajagopal, Raj Narayana Gadde, Deepanshu Yadvandu, Aishwarya Rajaram, Narasinga Rao Miniskar
Publikováno v:
ICIP
Adapting complex Convolution Neural Network (CNN) applications on embedded processors is a challenge due to the massive memory bandwidth and computational requirements. In particular, the CNN memory bandwidth requirement poses a huge challenge for th
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2852f4f7e82c752c3a8ec3c5f83ab592
https://doi.org/10.1109/icip.2018.8451706
https://doi.org/10.1109/icip.2018.8451706
Autor:
Chandra Kumar Ramasamy, Ashok Vishnoi, Vasanthakumar Rajagopal, Sirish Kumar Pasupuleti, Narasinga Rao Miniskar, Raj Narayana Gadde
Publikováno v:
ICIP
Deploying DNNs on embedded devices is a challenge because of their high memory and computational requirements. Performing DNN inference in lesser bit-width fixed point arithmetic is seen as a crucial step in realizing DNNs on embedded devices. State-
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::89dc1b988f7bd52aedda959052db0a57
https://doi.org/10.1109/icip.2018.8451268
https://doi.org/10.1109/icip.2018.8451268
Autor:
Vasanthakumar Rajagopal, Narasinga Rao Miniskar, Chandra Kumar Ramasamy, Ashok Vishnoi, Raj Narayana Gadde, Sirish Kumar Pasupuleti
Publikováno v:
ISCAS
Deep Learning based applications are becoming increasingly ubiquitous. The new generation smart phones are adapting lot of applications built on deep learning technology. However, adapting complex Deep Neural Network (DNN) applications on embedded pr
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d07852657d0c90217149b6b3363da26c
https://doi.org/10.1109/iscas.2018.8351294
https://doi.org/10.1109/iscas.2018.8351294