Zobrazeno 1 - 10
of 15
pro vyhledávání: '"Pramod Kumar Swami"'
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:
ICCE-Berlin
Deep Learning techniques like Convolutional Neural Networks (CNN) are the de-facto method for image classification with broad usage spanning across automotive, industrial, medicine, robotics etc. Efficient implementation of CNN inference on embedded
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::411b429bed74b1eebe7a773285071d74
https://doi.org/10.1109/icce-berlin.2018.8576251
https://doi.org/10.1109/icce-berlin.2018.8576251
Autor:
Daniel Brodeski, Oren Longman, Pramod Kumar Swami, Chethan Y. B. Kumar, Kedar Chitnis, Shankar Ram, Aishwarya Dubey, Shahar Villeval, Anshu Jain, Stanley Liu, Yashwant Dutt, Sandeep Rao, Piyali Goswami, Haim Ringel, Igal Bilik, Anil Kumar
Publikováno v:
2018 IEEE Radar Conference (RadarConf18).
Radars play a major role in providing sensing capabilities for active safety automotive applications. Multi-transmitter and multi-receiver radar systems are becoming popular in order to detect and classify objects in complex urban driving scenarios.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::09802d9ff7b514269d60e86b121b605e
https://doi.org/10.1109/radar.2018.8378587
https://doi.org/10.1109/radar.2018.8378587
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:
Brijesh Jadav, Pramod Kumar Swami, Victor Cheng, Kumar Desappan, Anshu Jain, Mihir Mody, Kedar Chitnis, Jesse Villarreal, Lucas Weaver
Publikováno v:
2017 IEEE International Conference on Consumer Electronics-Asia (ICCE-Asia).
Heterogeneous multi-core systems (CPU, GPU, HWA, DSP) are becoming the de-facto norm for multiple computer vision applications across automotive, robotics, AR/VR, and industrial machine vision. This creates a need for a software framework which reali
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::61c1c904f744b5b0d2d8d472fc320c7a
https://doi.org/10.1109/icce-asia.2017.8309323
https://doi.org/10.1109/icce-asia.2017.8309323
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, Aishwarya Dubey, Kedar Chitnis, Pragat Chaudhari, Piyali Goswami, Anshu Jain
Publikováno v:
2017 IEEE Radar Conference (RadarConf).
Automotive is an important application of radar. In collision avoidance applications, radar and camera are two main sensors with radar having a healthy share [16]. Usage of radar in the automotive space is expanding beyond range and velocity detectio
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1829a8824ef89dd17103668c3473309a
https://doi.org/10.1109/radar.2017.7944409
https://doi.org/10.1109/radar.2017.7944409
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:
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
Publikováno v:
ICCE
Lane departure warning (LDW) systems have gained a lot of interest over the last few years. EuroNCAP regulations mandate European car makers to have LDW system to get star rating. In this paper, we propose a simple image-based implementation of LDW s
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6bb53cfcceb175412fd8cf2e21f1f665
https://doi.org/10.1109/icce.2016.7430527
https://doi.org/10.1109/icce.2016.7430527