Zobrazeno 1 - 10
of 4 451
pro vyhledávání: '"Sengar, A."'
Autor:
Trudu, M., Possenti, A., Pilia, M., Bailes, M., Keane, E. F., Kramer, M., Balakrishnan, V., Bhandari, S., Bhat, N. D. R., Burgay, M., Cameron, A., Champion, D. J., Jameson, A., Johnston, S., Keith, M. J., Levin, L., Ng, C., Sengar, R., Tiburzi, C.
Publikováno v:
A&A 690, A204 (2024)
Current observational evidence reveals that fast radio bursts (FRBs) exhibit bandwidths ranging from a few dozen MHz to several GHz. Traditional FRB searches primarily employ matched filter methods on time series collapsed across the entire observati
Externí odkaz:
http://arxiv.org/abs/2408.14384
Autor:
Frail, Dale A., Polisensky, Emil, Hyman, Scott D., Cotton, W. M., Kassim, Namir E., Silverstein, Michele L., Sengar, Rahul, Kaplan, David L., Calore, Francesca, Berteaud, Joanna, Clavel, Maica, Geyer, Marisa, Legodi, Samuel, Krishnan, Vasaant, Buchner, Sarah, Camilo, Fernando
We report on the results of an image-based search for pulsar candidates toward the Galactic bulge. We used mosaic images from the MeerKAT radio telescope, that were taken as part of a 173 deg**2 survey of the bulge and Galactic center of our Galaxy a
Externí odkaz:
http://arxiv.org/abs/2407.01773
This study presents significant enhancements in human pose estimation using the MediaPipe framework. The research focuses on improving accuracy, computational efficiency, and real-time processing capabilities by comprehensively optimising the underly
Externí odkaz:
http://arxiv.org/abs/2406.15649
This study presents a novel driver drowsiness detection system that combines deep learning techniques with the OpenCV framework. The system utilises facial landmarks extracted from the driver's face as input to Convolutional Neural Networks trained t
Externí odkaz:
http://arxiv.org/abs/2406.15646
Autor:
Sengar, Sandeep Singh
Developing a robust object tracker is a challenging task due to factors such as occlusion, motion blur, fast motion, illumination variations, rotation, background clutter, low resolution and deformation across the frames. In the literature, lots of g
Externí odkaz:
http://arxiv.org/abs/2406.09914
In recent years, the study of artificial intelligence (AI) has undergone a paradigm shift. This has been propelled by the groundbreaking capabilities of generative models both in supervised and unsupervised learning scenarios. Generative AI has shown
Externí odkaz:
http://arxiv.org/abs/2405.11029
Object detection algorithms particularly those based on YOLO have demonstrated remarkable efficiency in balancing speed and accuracy. However, their application in brain tumour detection remains underexplored. This study proposes RepVGG-GELAN, a nove
Externí odkaz:
http://arxiv.org/abs/2405.03541
Autor:
Singh, Owen, Sengar, Sandeep Singh
Colorectal cancer contributes significantly to cancer-related mortality. Timely identification and elimination of polyps through colonoscopy screening is crucial in order to decrease mortality rates. Accurately detecting polyps in colonoscopy images
Externí odkaz:
http://arxiv.org/abs/2405.04288
Autor:
Ashwani, Swagata, Hegde, Kshiteesh, Mannuru, Nishith Reddy, Jindal, Mayank, Sengar, Dushyant Singh, Kathala, Krishna Chaitanya Rao, Banga, Dishant, Jain, Vinija, Chadha, Aman
With the rise of Large Language Models(LLMs), it has become crucial to understand their capabilities and limitations in deciphering and explaining the complex web of causal relationships that language entails. Current methods use either explicit or i
Externí odkaz:
http://arxiv.org/abs/2402.18139
Driver distraction is a principal cause of traffic accidents. In a study conducted by the National Highway Traffic Safety Administration, engaging in activities such as interacting with in-car menus, consuming food or beverages, or engaging in teleph
Externí odkaz:
http://arxiv.org/abs/2312.14577