Zobrazeno 1 - 10
of 3 799
pro vyhledávání: '"SHAHZAD, Muhammad"'
The proliferation of smartphones and other mobile devices provides a unique opportunity to make Advanced Driver Assistance Systems (ADAS) accessible to everyone in the form of an application empowered by low-cost Machine/Deep Learning (ML/DL) models
Externí odkaz:
http://arxiv.org/abs/2410.19336
There is a need for empathetic and coherent responses in automated chatbot-facilitated psychotherapy sessions. This study addresses the challenge of enhancing the emotional and contextual understanding of large language models (LLMs) in psychiatric a
Externí odkaz:
http://arxiv.org/abs/2410.01306
Autor:
Luginov, Albert, Shahzad, Muhammad
We introduce NimbleD, an efficient self-supervised monocular depth estimation learning framework that incorporates supervision from pseudo-labels generated by a large vision model. This framework does not require camera intrinsics, enabling large-sca
Externí odkaz:
http://arxiv.org/abs/2408.14177
In the realm of deploying Machine Learning-based Advanced Driver Assistance Systems (ML-ADAS) into real-world scenarios, adverse weather conditions pose a significant challenge. Conventional ML models trained on clear weather data falter when faced w
Externí odkaz:
http://arxiv.org/abs/2407.02581
Autor:
Spencer, Jaime, Tosi, Fabio, Poggi, Matteo, Arora, Ripudaman Singh, Russell, Chris, Hadfield, Simon, Bowden, Richard, Zhou, GuangYuan, Li, ZhengXin, Rao, Qiang, Bao, YiPing, Liu, Xiao, Kim, Dohyeong, Kim, Jinseong, Kim, Myunghyun, Lavreniuk, Mykola, Li, Rui, Mao, Qing, Wu, Jiang, Zhu, Yu, Sun, Jinqiu, Zhang, Yanning, Patni, Suraj, Agarwal, Aradhye, Arora, Chetan, Sun, Pihai, Jiang, Kui, Wu, Gang, Liu, Jian, Liu, Xianming, Jiang, Junjun, Zhang, Xidan, Wei, Jianing, Wang, Fangjun, Tan, Zhiming, Wang, Jiabao, Luginov, Albert, Shahzad, Muhammad, Hosseini, Seyed, Trajcevski, Aleksander, Elder, James H.
This paper discusses the results of the third edition of the Monocular Depth Estimation Challenge (MDEC). The challenge focuses on zero-shot generalization to the challenging SYNS-Patches dataset, featuring complex scenes in natural and indoor settin
Externí odkaz:
http://arxiv.org/abs/2404.16831
Publikováno v:
Measuring Business Excellence, 2024, Vol. 28, Issue 3/4, pp. 415-425.
Externí odkaz:
http://www.emeraldinsight.com/doi/10.1108/MBE-04-2024-0052
Autor:
Shahzad, Muhammad Umar
Publikováno v:
The Bottom Line, 2024, Vol. 37, Issue 4, pp. 454-472.
Externí odkaz:
http://www.emeraldinsight.com/doi/10.1108/BL-10-2023-0278
Multi-modal problems can be effectively addressed using multiple hypothesis frameworks, but integrating these frameworks into learning models poses significant challenges. This paper introduces a Structured Radial Basis Function Network (s-RBFN) as a
Externí odkaz:
http://arxiv.org/abs/2309.00781
Autor:
de Gélis, Iris, Saha, Sudipan, Shahzad, Muhammad, Corpetti, Thomas, Lefèvre, Sébastien, Zhu, Xiao Xiang
Publikováno v:
ISPRS Open Journal of Photogrammetry and Remote Sensing Volume 9, August 2023, 100044
Change detection from traditional \added{2D} optical images has limited capability to model the changes in the height or shape of objects. Change detection using 3D point cloud \added{from photogrammetry or LiDAR surveying} can fill this gap by provi
Externí odkaz:
http://arxiv.org/abs/2305.03529
Autor:
Nigar, Natasha1 (AUTHOR) natasha@uet.edu.pk, Shahzad, Muhammad Kashif2 (AUTHOR), Faisal, Hafiz Muhammad3 (AUTHOR), Ajagbe, Sunday Adeola4 (AUTHOR) saajagbe@pgschool.lautech.edu.ng, Adigun, Matthew O.5 (AUTHOR), F. F. Areed, Nihal (AUTHOR)
Publikováno v:
Journal of Electrical & Computer Engineering. 11/16/2024, Vol. 2024, p1-11. 11p.