Zobrazeno 1 - 10
of 7 519
pro vyhledávání: '"Ramani P"'
Autor:
Yasith Mathangasinghe, Sameera Wijayawardhana, Udeshika Perera, Ramani Punchihewa, Saman Pradeep
Publikováno v:
Thoracic Cancer, Vol 15, Iss 4, Pp 347-349 (2024)
Abstract The prevalence of lung cancer is steadily increasing globally, and it is projected to become the second most prevalent cancer in men by 2030. Lung cancer is the leading cause of cancer‐related deaths worldwide, accounting for approximately
Externí odkaz:
https://doaj.org/article/7a30e5b2108b4f9694d8e0df4022941b
Publikováno v:
Bibechana, Vol 20, Iss 3 (2023)
Candle soot, carbon samples prepared by flame-soot method, was characterized and investigated for its catalytic ability for the reduction of tri-iodide ions aiming to substitute expensive platinum based electrode used in dye-sensitized solar cells (D
Externí odkaz:
https://doaj.org/article/27cf8813f5a7489cb82b54c88c493058
Publikováno v:
Journal of Orofacial Sciences, Vol 15, Iss 1, Pp 92-98 (2023)
Introduction: Peripheral blood smear examination is one of the most crucial diagnostic methods used in the clinical laboratories. The aim of the current study is to assess the efficacy and quality of smears produced by the innovative smear hub in com
Externí odkaz:
https://doaj.org/article/bb4ad1e0540c41d1bf0a44f028837d34
We study the problem of estimating the body movements of a camera wearer from egocentric videos. Current methods for ego-body pose estimation rely on temporally dense sensor data, such as IMU measurements from spatially sparse body parts like the hea
Externí odkaz:
http://arxiv.org/abs/2411.03561
Autor:
Sakshi, S, Tyagi, Utkarsh, Kumar, Sonal, Seth, Ashish, Selvakumar, Ramaneswaran, Nieto, Oriol, Duraiswami, Ramani, Ghosh, Sreyan, Manocha, Dinesh
The ability to comprehend audio--which includes speech, non-speech sounds, and music--is crucial for AI agents to interact effectively with the world. We present MMAU, a novel benchmark designed to evaluate multimodal audio understanding models on ta
Externí odkaz:
http://arxiv.org/abs/2410.19168
Graph distillation has emerged as a promising avenue to enable scalable training of GNNs by compressing the training dataset while preserving essential graph characteristics. Our study uncovers significant shortcomings in current graph distillation t
Externí odkaz:
http://arxiv.org/abs/2410.17579
Dark matter's existence is known thanks to its gravitational interaction with Standard Model particles, but it remains unknown whether this is the only force present between them. While many searches for such new interactions with dark matter focus o
Externí odkaz:
http://arxiv.org/abs/2410.07324
Autor:
Fan, Xing, Gabrielse, Gerald, Graham, Peter W., Ramani, Harikrishnan, Wong, Samuel S. Y., Xiao, Yawen
We propose using highly excited cyclotron states of a trapped electron to detect meV axion and dark photon dark matter, marking a significant improvement over our previous proposal and demonstration [Phys. Rev. Lett. 129, 261801]. When the axion mass
Externí odkaz:
http://arxiv.org/abs/2410.05549
Autor:
Ghosh, Sreyan, Kumar, Sonal, Evuru, Chandra Kiran Reddy, Nieto, Oriol, Duraiswami, Ramani, Manocha, Dinesh
Open-vocabulary audio-language models, like CLAP, offer a promising approach for zero-shot audio classification (ZSAC) by enabling classification with any arbitrary set of categories specified with natural language prompts. In this paper, we propose
Externí odkaz:
http://arxiv.org/abs/2409.09213
While models in audio and speech processing are becoming deeper and more end-to-end, they as a consequence need expensive training on large data, and are often brittle. We build on a classical model of human hearing and make it differentiable, so tha
Externí odkaz:
http://arxiv.org/abs/2409.08997