Zobrazeno 1 - 7
of 7
pro vyhledávání: '"Sirish Kumar Pasupuleti"'
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
Publikováno v:
ICIP
Deploying Convolution Neural Networks (CNN) based computer vision applications on low-power embedded devices is challenging due to massive computation and memory bandwidth requirements. Research is on-going on faster algorithms, network pruning, and
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7a8f8b3ea16298a71d165801aa5e6e3a
https://doi.org/10.1109/icip.2017.8297115
https://doi.org/10.1109/icip.2017.8297115
Publikováno v:
ICASSP
As world is moving towards Ultra High Definition (UHD) content and display technology, high quality visual content is becoming a necessity. Deblocking filter is one of the tools used in today's video coding standards to enhance the quality of compres
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f8b56b01abb342951e46f4d0963768ca
https://doi.org/10.1109/icassp.2016.7471836
https://doi.org/10.1109/icassp.2016.7471836
Publikováno v:
ICCD
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e18a92bfecf5a21826db66570a06b08d
https://doi.org/10.1109/iccd.2014.6974703
https://doi.org/10.1109/iccd.2014.6974703