Zobrazeno 1 - 10
of 22 193
pro vyhledávání: '"A. Vignesh"'
Autor:
G. Sathiyaraj, A. Vignesh, K. Priyanka, K.S. Neethu, D. Badhmapriya, K. Preethi, N. Dharmaraj, M.V. Kaveri
Publikováno v:
Results in Chemistry, Vol 6, Iss , Pp 101141- (2023)
This work describes the fabrication of a carbazole derivative 1 namely (E)-5-(diethylamino)-2-((9-ethyl-9H-carbazol-3-yl)imino)methyl)phenol(1) based colorimetric probe for the selective detection of copper (II) ions. The as-prepared carbazole deriva
Externí odkaz:
https://doaj.org/article/da0fb0d754f14b45bd2c35a52dd5859e
In this study, we investigate the under-explored intervention planning aimed at disseminating accurate information within dynamic opinion networks by leveraging learning strategies. Intervention planning involves identifying key nodes (search) and ex
Externí odkaz:
http://arxiv.org/abs/2410.14091
Recent progress in audio-language modeling, such as automated audio captioning, has benefited from training on synthetic data generated with the aid of large-language models. However, such approaches for environmental sound captioning have primarily
Externí odkaz:
http://arxiv.org/abs/2410.12028
This paper compares scale-invariant (SIFT) and scale-variant (ORB) feature detection methods, alongside our novel feature detector, IntFeat, specifically applied to lunar imagery. We evaluate these methods using low (128x128) and high-resolution (102
Externí odkaz:
http://arxiv.org/abs/2410.11118
Autor:
Hsu, Pin-Lun, Dai, Yun, Kothapalli, Vignesh, Song, Qingquan, Tang, Shao, Zhu, Siyu, Shimizu, Steven, Sahni, Shivam, Ning, Haowen, Chen, Yanning
Training Large Language Models (LLMs) efficiently at scale presents a formidable challenge, driven by their ever-increasing computational demands and the need for enhanced performance. In this work, we introduce Liger-Kernel, an open-sourced set of T
Externí odkaz:
http://arxiv.org/abs/2410.10989
Autor:
Viswanathan, Vignesh Kottayam, Sumathy, Vidya, Kanellakis, Christoforos, Nikolakopoulos, George
In this work, we present an autonomous inspection framework for remote sensing tasks in active open-pit mines. Specifically, the contributions are focused towards developing a methodology where an initial approximate operator-defined inspection plan
Externí odkaz:
http://arxiv.org/abs/2410.10256
Autor:
Sundaresha, Vignesh, Shanbhag, Naresh
The ubiquitous deployment of deep learning systems on resource-constrained Edge devices is hindered by their high computational complexity coupled with their fragility to out-of-distribution (OOD) data, especially to naturally occurring common corrup
Externí odkaz:
http://arxiv.org/abs/2410.07691
Optimizing framerate for a given bitrate-spatial resolution pair in adaptive video streaming is essential to maintain perceptual quality while considering decoding complexity. Low framerates at low bitrates reduce compression artifacts and decrease d
Externí odkaz:
http://arxiv.org/abs/2410.00849
Autor:
Elnoor, Mohamed, Weerakoon, Kasun, Seneviratne, Gershom, Xian, Ruiqi, Guan, Tianrui, Jaffar, Mohamed Khalid M, Rajagopal, Vignesh, Manocha, Dinesh
We present a novel autonomous robot navigation algorithm for outdoor environments that is capable of handling diverse terrain traversability conditions. Our approach, VLM-GroNav, uses vision-language models (VLMs) and integrates them with physical gr
Externí odkaz:
http://arxiv.org/abs/2409.20445
Pareto-front optimization is crucial for addressing the multi-objective challenges in video streaming, enabling the identification of optimal trade-offs between conflicting goals such as bitrate, video quality, and decoding complexity. This paper exp
Externí odkaz:
http://arxiv.org/abs/2409.18713