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pro vyhledávání: '"A. Sravan Kumar"'
Image Classification and Video Action Recognition are perhaps the two most foundational tasks in computer vision. Consequently, explaining the inner workings of trained deep neural networks is of prime importance. While numerous efforts focus on expl
Externí odkaz:
http://arxiv.org/abs/2404.09067
The design of reliable and efficient codes for channels with feedback remains a longstanding challenge in communication theory. While significant improvements have been achieved by leveraging deep learning techniques, neural codes often suffer from h
Externí odkaz:
http://arxiv.org/abs/2403.10751
Progress in designing channel codes has been driven by human ingenuity and, fittingly, has been sporadic. Polar codes, developed on the foundation of Arikan's polarization kernel, represent the latest breakthrough in coding theory and have emerged as
Externí odkaz:
http://arxiv.org/abs/2402.08864
Tailoring polar code construction for decoding algorithms beyond successive cancellation has remained a topic of significant interest in the field. However, despite the inherent nested structure of polar codes, the use of sequence models in polar cod
Externí odkaz:
http://arxiv.org/abs/2401.17188
Autor:
Kim, Heasung, Ankireddy, Sravan Kumar
In this work, we consider the problem of network parameter optimization for rate maximization. We frame this as a joint optimization problem of power control, beam forming, and interference cancellation. We consider the setting where multiple Base St
Externí odkaz:
http://arxiv.org/abs/2310.08660
Publikováno v:
Annals of Indian Academy of Neurology, Vol 27, Iss 5, Pp 573-575 (2024)
Externí odkaz:
https://doaj.org/article/40ad126fe9004a9fac4bc336a041dbf3
Autor:
Li, Po-han, Ankireddy, Sravan Kumar, Zhao, Ruihan, Mahjoub, Hossein Nourkhiz, Moradi-Pari, Ehsan, Topcu, Ufuk, Chinchali, Sandeep, Kim, Hyeji
Publikováno v:
NeurIPS 2023
Efficient compression of correlated data is essential to minimize communication overload in multi-sensor networks. In such networks, each sensor independently compresses the data and transmits them to a central node due to limited communication bandw
Externí odkaz:
http://arxiv.org/abs/2305.15523
In modern communication systems with feedback, there are increasingly more scenarios where the transmitter has much less power than the receiver (e.g., medical implant devices), which we refer to as noise-asymmetric channels. For such channels, the f
Externí odkaz:
http://arxiv.org/abs/2302.10170
In this paper, we introduce a novel network that generates semantic, instance, and part segmentation using a shared encoder and effectively fuses them to achieve panoptic-part segmentation. Unifying these three segmentation problems allows for mutual
Externí odkaz:
http://arxiv.org/abs/2212.07671
Autor:
Sravanthi, Mangali1,2 (AUTHOR) sravanthi.engg@mriet.ac.in, Gunturi, Sravan Kumar1 (AUTHOR) sravankumar.gunturi@gmail.com, Chinnaiah, Mangali Chinna3,4 (AUTHOR) siewkei_lam@pmail.ntu.edu.sg, Lam, Siew-Kei4 (AUTHOR), Vani, G. Divya3 (AUTHOR) mudasar.basha@bvrit.ac.in, Basha, Mudasar3 (AUTHOR) harikrishna.dodde@bvrit.ac.in, Janardhan, Narambhatla5 (AUTHOR) njanardhan_mech@cbit.ac.in, Krishna, Dodde Hari3 (AUTHOR) sanjay.dubey@bvrit.ac.in, Dubey, Sanjay3 (AUTHOR)
Publikováno v:
Sensors (14248220). Nov2024, Vol. 24 Issue 21, p6986. 24p.