Zobrazeno 1 - 10
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pro vyhledávání: '"Renjith, P."'
Autor:
Wei, Ran, Lee, Joseph, Wakayama, Shohei, Tschantz, Alexander, Heins, Conor, Buckley, Christopher, Carenbauer, John, Thiruvengada, Hari, Albarracin, Mahault, de Prado, Miguel, Horling, Petter, Winzell, Peter, Rajagopal, Renjith
Predicting future trajectories of nearby objects, especially under occlusion, is a crucial task in autonomous driving and safe robot navigation. Prior works typically neglect to maintain uncertainty about occluded objects and only predict trajectorie
Externí odkaz:
http://arxiv.org/abs/2410.10653
Autor:
R, Renjith Kumar, Geethika, B R, Verma, Nancy, Chaudhari, Vishnu, Dave, Janvi, Joshi, Hem Chandra, Thomas, Jinto
In this work, we report an innovative pump-probe based experimental set up, to study the melting, subsequent evaporation, plasma formation and redeposition in a thin film coated on a glass substrate under different ambient conditions and laser fluenc
Externí odkaz:
http://arxiv.org/abs/2410.07755
Laser-induced breakdown spectroscopy (LIBS) is a well-established technique widely used in fundamental research and diverse practical fields. Polarization-resolved LIBS, a variant of this technique, aims to improve the sensitivity, which is a critica
Externí odkaz:
http://arxiv.org/abs/2410.07390
Autor:
Prasad, Renjith, Shyalika, Chathurangi, Zand, Ramtin, Kalach, Fadi El, Venkataramanan, Revathy, Harik, Ramy, Sheth, Amit
Publikováno v:
Predictive Models in Engineering Applications special session (MLPMEA) at International Conference on Machine Learning and Applications (ICMLA) 2024
Anomaly detection in manufacturing pipelines remains a critical challenge, intensified by the complexity and variability of industrial environments. This paper introduces AssemAI, an interpretable image-based anomaly detection system tailored for sma
Externí odkaz:
http://arxiv.org/abs/2408.02181
Continual learning (CL) remains a significant challenge for deep neural networks, as it is prone to forgetting previously acquired knowledge. Several approaches have been proposed in the literature, such as experience rehearsal, regularization, and p
Externí odkaz:
http://arxiv.org/abs/2405.13978
Continual learning (CL) remains one of the long-standing challenges for deep neural networks due to catastrophic forgetting of previously acquired knowledge. Although rehearsal-based approaches have been fairly successful in mitigating catastrophic f
Externí odkaz:
http://arxiv.org/abs/2404.18161
Federated learning is a technique of decentralized machine learning. that allows multiple parties to collaborate and learn a shared model without sharing their raw data. Our paper proposes a federated learning framework for intrusion detection in Int
Externí odkaz:
http://arxiv.org/abs/2311.13800
Autor:
Roy, Renjith Mathew, Pal, Sudip, Yang, Run, Roh, Seulki, Shin, Soohyeon, Park, Tae Beom, Park, Tuson, Dressel, Martin
The heavy-fermion compound CeRhIn$_5$ can be tuned through a quantum critical point, when In is partially replaced by Sn. This way additional charge carriers are introduced and the antiferromagnetic order is gradually suppressed to zero temperature.
Externí odkaz:
http://arxiv.org/abs/2310.16689
Polarized emission carries captivating information and can help understand various elementary processes involving collisions within the plasma as well as in radiative transitions. In this work, we investigate the spatio-temporal dependence of the emi
Externí odkaz:
http://arxiv.org/abs/2309.11223
Autor:
Venkataramanan, Revathy, Roy, Kaushik, Raj, Kanak, Prasad, Renjith, Zi, Yuxin, Narayanan, Vignesh, Sheth, Amit
As people become more aware of their food choices, food computation models have become increasingly popular in assisting people in maintaining healthy eating habits. For example, food recommendation systems analyze recipe instructions to assess nutri
Externí odkaz:
http://arxiv.org/abs/2306.01805