Zobrazeno 1 - 10
of 1 649
pro vyhledávání: '"Purushotham P."'
Autor:
Shankar S. Siva, Srinivas S., Kodati Sarangam, punati Kondalarao, Purushotham P., Gurnadha Gupta Koppuravuri, Manikandan G., Nagendra Kumar Y.J., Dutt Amit
Publikováno v:
MATEC Web of Conferences, Vol 392, p 01105 (2024)
Parking spots have become a prevalent concern in urban growth. The number of automobiles is increasing faster than accessible parking spaces. This problem is addressed by implementing an Internet of Things (IoT)-based Parking Surveillance Scheme (IoT
Externí odkaz:
https://doaj.org/article/cf38127eaf0f4d8dadd261f9da6f4495
Autor:
Mostafa, Seraj Al Mahmud, Faruque, Omar, Wang, Chenxi, Yue, Jia, Purushotham, Sanjay, Wang, Jianwu
Atmospheric gravity waves occur in the Earths atmosphere caused by an interplay between gravity and buoyancy forces. These waves have profound impacts on various aspects of the atmosphere, including the patterns of precipitation, cloud formation, ozo
Externí odkaz:
http://arxiv.org/abs/2408.14674
The increasing threat of sea level rise due to climate change necessitates a deeper understanding of ice sheet structures. This study addresses the need for accurate ice sheet data interpretation by introducing a suite of quantitative metrics designe
Externí odkaz:
http://arxiv.org/abs/2407.09535
Autor:
Bridges, Patrick G., Skjellum, Anthony, Suggs, Evan D., Schafer, Derek, Bangalore, Purushotham V.
GPU-enhanced architectures are now dominant in HPC systems, but message-passing communication involving GPUs with MPI has proven to be both complex and expensive, motivating new approaches that lower such costs. We compare and contrast stream/graph-
Externí odkaz:
http://arxiv.org/abs/2406.05594
Autor:
Adnan, Muhammad, Arunkumar, Akhil, Jain, Gaurav, Nair, Prashant J., Soloveychik, Ilya, Kamath, Purushotham
Publikováno v:
Proceedings of the 7th Annual Conference on Machine Learning and Systems (MLSys), 2024
Transformers have emerged as the underpinning architecture for Large Language Models (LLMs). In generative language models, the inference process involves two primary phases: prompt processing and token generation. Token generation, which constitutes
Externí odkaz:
http://arxiv.org/abs/2403.09054
Autor:
Madambakam, Prameela, Rajmohan, Shathanaa, Sharma, Himangshu, Gupta, Tummepalli Anka Chandrahas Purushotham
Legal Judgment Prediction (LJP) is a judicial assistance system that recommends the legal components such as applicable statues, prison term and penalty term by analyzing the given input case document. Indian legal system is in the need of technical
Externí odkaz:
http://arxiv.org/abs/2312.07979
Autor:
Ordun, Catherine, Cha, Alexandra, Raff, Edward, Purushotham, Sanjay, Kwok, Karen, Rule, Mason, Gulley, James
Publikováno v:
2nd Annual Artificial Intelligence over Infrared Images for Medical Applications Workshop 2023
Since thermal imagery offers a unique modality to investigate pain, the U.S. National Institutes of Health (NIH) has collected a large and diverse set of cancer patient facial thermograms for AI-based pain research. However, differing angles from cam
Externí odkaz:
http://arxiv.org/abs/2308.12271
Autor:
Hasan, Zahid, Faridee, Abu Zaher Md, Ahmed, Masud, Purushotham, Sanjay, Kwon, Heesung, Lee, Hyungtae, Roy, Nirmalya
Novel Categories Discovery (NCD) aims to cluster novel data based on the class semantics of known classes using the open-world partial class space annotated dataset. As an alternative to the traditional pseudo-labeling-based approaches, we leverage t
Externí odkaz:
http://arxiv.org/abs/2307.03856
Publikováno v:
2023, 7th IEEE International Joint Conference on Biometrics (IJCB)
For a variety of biometric cross-spectral tasks, Visible-Thermal (VT) facial pairs are used. However, due to a lack of calibration in the lab, photographic capture between two different sensors leads to severely misaligned pairs that can lead to poor
Externí odkaz:
http://arxiv.org/abs/2306.06505
Autor:
Hasan, Zahid, Ahmed, Masud, Faridee, Abu Zaher Md, Purushotham, Sanjay, Kwon, Heesung, Lee, Hyungtae, Roy, Nirmalya
Novel Categories Discovery (NCD) facilitates learning from a partially annotated label space and enables deep learning (DL) models to operate in an open-world setting by identifying and differentiating instances of novel classes based on the labeled
Externí odkaz:
http://arxiv.org/abs/2304.07354