Zobrazeno 1 - 10
of 10
pro vyhledávání: '"Ankur Deshwal"'
Publikováno v:
IEEE Access, Vol 10, Pp 124990-124998 (2022)
Can we perform Neural Architecture Search (NAS) with a smaller subset of target dataset and still fair better in terms of performance with significant reduction in search cost? In this work, we propose a method, called DistilNAS, which utilizes a cur
Externí odkaz:
https://doaj.org/article/08f75ed939494c32925b0a547abf7254
Publikováno v:
Journal of Ultrasonography
Aim: The aims of our study were to evaluate cases of extremity pain or swelling in paediatric patients using USG to diagnose acute osteomyelitis, and correlate USG findings with MRI findings. Material and methods: 18 paediatric patients with extremit
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::aec81689298d9d71d2528169310fbce4
https://doi.org/10.15557/jou.2021.0005
https://doi.org/10.15557/jou.2021.0005
Autor:
Ankur Deshwal, Chetan Sood
Publikováno v:
Journal of Research and Practice on the Musculoskeletal System. :60-67
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::41b0ec7c4d2da880f7ffee096875963c
https://doi.org/10.22540/jrpms-04-060
https://doi.org/10.22540/jrpms-04-060
Autor:
Ankur Deshwal, Ujjawal Chugh, Arnab Mitra, Seungwon Lee, Kavitha T. Madhu, Joon-Ho Song, Aditi Saluja
Publikováno v:
ISCAS
Deployment of Deep Neural Networks (DNNs) on edge devices is highly desirable to address user privacy concerns and minimize the turnaround time of AI applications. However, the execution of DNN models on a battery-operated device requires a highly op
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c7b58db99ac93e5f01bfcd50c82bfff7
https://doi.org/10.1109/iscas51556.2021.9401783
https://doi.org/10.1109/iscas51556.2021.9401783
Publikováno v:
ISCAS
As throughput of neural network accelerator datapaths have grown, memory has consistently fallen behind. Although attempts have been made to improve performance of neural networks via approaches such as batching, several layers often starve for memor
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7c36c0f05674b394206f447dc33cbaf0
https://doi.org/10.1109/iscas51556.2021.9401315
https://doi.org/10.1109/iscas51556.2021.9401315
Autor:
Ankur Deshwal, Aditi Saluja, N. P. Swaroop, Ujjawal Chugh, Joon-Ho Song, Seungwon Lee, Arnab Mitra
Publikováno v:
ISCAS
Deployment of Deep Neural Networks (DNNs) on edge devices can significantly increase the utility of DNNs for a variety of applications. However executing DNN models on the edge device is still a major challenge, as heavy computation and memory bandwi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ad2e496d6d01420d94ba8c918f1cd00b
https://doi.org/10.1109/iscas51556.2021.9401141
https://doi.org/10.1109/iscas51556.2021.9401141
Publikováno v:
ISCAS
Modern Artificial Intelligence (AI) systems deploy Convolution Neural Networks (CNN) as they offer very high accuracy. Computational complexity of CNNs necessitates hardware acceleration, especially in mobile phones and other hand held devices due to
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::686033a4597bafc4bb874a660eeba2e4
https://doi.org/10.1109/iscas45731.2020.9180403
https://doi.org/10.1109/iscas45731.2020.9180403
Publikováno v:
ICME
Advent of deep neural networks has revolutionized Computer Vision. However, designing of such models with high accuracy and low computation requirements is a difficult task and needs extensive human expertise. Recent advances in Neural Architecture S
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5ae57bf07c697cabda09ebea9f8f82e8
https://doi.org/10.1109/icme46284.2020.9102879
https://doi.org/10.1109/icme46284.2020.9102879
Autor:
Youngsam Shin, Seok Joong Hwang, Jaedon Lee, Soojung Ryu, Dong-hoon Yoo, Ankur Deshwal, Jeongwook Kim, Won-Jong Lee
Publikováno v:
SIGGRAPH ASIA Mobile Graphics and Interactive Applications
This paper presents a shading language compiler optimized for a mobile ray tracing acclerator, i.e., SGRT (Samsung GPU Ray Tracing). By the compiler, application development productivity has been dramatically improved: 1) as an application-specific a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5a2ee556cb5e9296c62550f2e3df5140
https://doi.org/10.1145/2669062.2669068
https://doi.org/10.1145/2669062.2669068
Publikováno v:
ICCC
Wireless Sensors have seen a lot of applications in our daily lives in the recent years. The market has been flooded with high end consumer electronics using wireless sensor technology. However, most of the current technologies require the sensor to
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e2c86b08b45ad4ad52142ff3e2ff24f2
https://doi.org/10.1109/iccchina.2012.6356972
https://doi.org/10.1109/iccchina.2012.6356972