Zobrazeno 1 - 10
of 26
pro vyhledávání: '"Soyeb Nagori"'
Publikováno v:
2019 IEEE International Conference on Electronics, Computing and Communication Technologies (CONECCT).
Within the universe of automated driving (AD) applications, automated valet parking (AVP) is especially attractive in terms of opportunities and adoption. A camera is one of the commonly favored perception sensors in the AVP application. Where the de
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::021ce7269855fd528a06f721a9237e7f
https://doi.org/10.1109/conecct47791.2019.9012933
https://doi.org/10.1109/conecct47791.2019.9012933
Publikováno v:
ICCE-Berlin
Automated driving functions, like highway driving and parking assist, are getting increasing deployed in high-end cars with the trend moving towards the self-driving car. With the advent of deep learning, many traditional computer vision techniques h
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5be61756f04956355b7141072e22b43b
https://doi.org/10.1109/icce-berlin.2018.8576190
https://doi.org/10.1109/icce-berlin.2018.8576190
Publikováno v:
ISQED
Automated driving functions, like highway driving and parking assist, are increasingly getting deployed in high-end cars with the ultimate goal of realizing self-driving car using Deep learning techniques like convolution neural network (CNN). For ma
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::cec5ccb768149ae01591a29650fb83fd
https://doi.org/10.1109/isqed.2018.8357325
https://doi.org/10.1109/isqed.2018.8357325
Autor:
Manu Mathew, Nikitha Vallurupalli, Girish Varma, Sriharsha Annamaneni, Soyeb Nagori, C. V. Jawahar
Publikováno v:
CVPR Workshops
Deep CNNs for semantic segmentation have high memory and run time requirements. Various approaches have been proposed to make CNNs efficient like grouped, shuffled, depth-wise separable convolutions. We study the effectiveness of these techniques on
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::08e9bfa62f3b1480290f10e5affb7fdf
Publikováno v:
CVPR Workshops
This paper presents methods to reduce the complexity of convolutional neural networks (CNN). These include: (1) A method to quickly and easily sparsify a given network. (2) Fine tune the sparse network to obtain the lost accuracy back (3) Quantize th
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::79494d1b97673736d44bdacc0964a094
https://doi.org/10.1109/cvprw.2017.46
https://doi.org/10.1109/cvprw.2017.46
Autor:
Pramod Kumar Swami, Shyam Jagannathan, Manu Mathew, Anshu Jain, Deepak Kumar Poddar, Prashanth Viswanath, Desappan Kumar, Soyeb Nagori
Publikováno v:
ICCE
Understanding of 3D surrounding is an important problem in Advanced Driver Assistance Systems (ADAS). Structure from Motion (SfM) is well known computer vision technique for estimating 3D structure from 2D image sequences. Inherent complexities of th
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2e4af2696a31f4f7a3ac4ad18784933c
https://doi.org/10.1109/icce.2017.7889295
https://doi.org/10.1109/icce.2017.7889295
Autor:
Shyam Jagannathan, Kumar Desappan, Pramod Swami, Manu Mathew, Soyeb Nagori, Kedar Chitnis, Yogesh Marathe, Deepak Poddar, Suriya Narayanan, Anshu Jain
Publikováno v:
ICCE
Identifying real world 3D objects such as pedestrians, vehicles and traffic signs using 2D images is a challenging task. There are multiple approaches to tackle this problem with varying degree of detection accuracy and implementation complexity. Som
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::39641cbf9f45c85f612b9baf10ec25b5
https://doi.org/10.1109/icce.2017.7889296
https://doi.org/10.1109/icce.2017.7889296
Autor:
Manu Mathew, Kedar Chitnis, Anshu Jain, Hrushikesh Garud, Mihir Mody, Pramod Kumar Swami, Kumar Desappan, Prashanth Viswanath, Mayank Mangla, Shashank Dabral, Shyam Jagannathan, Vikram Appia, Soyeb Nagori, Sujith Shivalingappa, Deepak Kumar Poddar
Publikováno v:
CVPR Workshops
Advanced driver assistance systems (ADAS) are becoming more and more popular. Lot of the ADAS applications such as Lane departure warning (LDW), Forward Collision Warning (FCW), Automatic Cruise Control (ACC), Auto Emergency Braking (AEB), Surround V
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d6057343aed31ff6033a3b3a7abd8332
https://doi.org/10.1109/cvprw.2016.107
https://doi.org/10.1109/cvprw.2016.107
Autor:
Pramod Kumar Swami, Zoran Nikolic, Manu Mathew, Anshu Jain, Prashanth Viswanath, Mihir Mody, Soyeb Nagori, Kumar Desappan, Shyam Jagannathan, Hrushikesh Garud, Kedar Chitnis, Deepak Kumar Poddar
Publikováno v:
HiPC
Advanced driver assistance systems (ADAS) are designed to increase driver's situational awareness and road safety by providing essential information, warning and automatic intervention to reduce the possibility/severity of an accident. Of the various
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9603d18b47f244aaa57d29b3b6aa5c61
https://doi.org/10.1109/hipc.2015.56
https://doi.org/10.1109/hipc.2015.56
Publikováno v:
Electronic Imaging. 30:164-1
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f186bce4695b0d74df074dbf3bdf98f6
https://doi.org/10.2352/issn.2470-1173.2018.17.avm-164
https://doi.org/10.2352/issn.2470-1173.2018.17.avm-164