Zobrazeno 1 - 10
of 29
pro vyhledávání: '"Narayanan, Praveen"'
Image classification with deep neural networks has seen a surge of technological breakthroughs with promising applications in areas such as face recognition, medical imaging, and autonomous driving. In engineering problems, however, such as high-spee
Externí odkaz:
http://arxiv.org/abs/2207.09609
Autor:
Long, Yunfei, Morris, Daniel, Liu, Xiaoming, Castro, Marcos, Chakravarty, Punarjay, Narayanan, Praveen
A distinctive feature of Doppler radar is the measurement of velocity in the radial direction for radar points. However, the missing tangential velocity component hampers object velocity estimation as well as temporal integration of radar sweeps in d
Externí odkaz:
http://arxiv.org/abs/2108.10637
Autor:
Long, Yunfei, Morris, Daniel, Liu, Xiaoming, Castro, Marcos, Chakravarty, Punarjay, Narayanan, Praveen
While radar and video data can be readily fused at the detection level, fusing them at the pixel level is potentially more beneficial. This is also more challenging in part due to the sparsity of radar, but also because automotive radar beams are muc
Externí odkaz:
http://arxiv.org/abs/2106.02778
Generative Adversarial Networks (GANs) are now widely used for photo-realistic image synthesis. In applications where a simulated image needs to be translated into a realistic image (sim-to-real), GANs trained on unpaired data from the two domains ar
Externí odkaz:
http://arxiv.org/abs/2001.09257
We present a voice conversion solution using recurrent sequence to sequence modeling for DNNs. Our solution takes advantage of recent advances in attention based modeling in the fields of Neural Machine Translation (NMT), Text-to-Speech (TTS) and Aut
Externí odkaz:
http://arxiv.org/abs/1907.07769
We present a Deep Learning based system for the twin tasks of localization and obstacle avoidance essential to any mobile robot. Our system learns from conventional geometric SLAM, and outputs, using a single camera, the topological pose of the camer
Externí odkaz:
http://arxiv.org/abs/1902.02086
Probabilistic programming languages are valuable because they allow domain experts to express probabilistic models and inference algorithms without worrying about irrelevant details. However, for decades there remained an important and popular class
Externí odkaz:
http://arxiv.org/abs/1805.06562
Autor:
NARAYANAN, PRAVEEN1 pravnar@indiana.edu, CHUNG-CHIEH SHAN1 ccshan@indiana.edu
Publikováno v:
ACM Transactions on Programming Languages & Systems. Apr2020, Vol. 42 Issue 2, p1-60. 60p.
Publikováno v:
In Proceedings of the Combustion Institute 2011 33(2):2539-2546
Autor:
Narayanan, Praveen, Trouvé, Arnaud
Publikováno v:
In Proceedings of the Combustion Institute 2009 32(1):1481-1489