Zobrazeno 1 - 10
of 3 455
pro vyhledávání: '"MUNIR, MUHAMMAD"'
Autor:
Danish, Muhammad Sohail, Munir, Muhammad Akhtar, Shah, Syed Roshaan Ali, Kuckreja, Kartik, Khan, Fahad Shahbaz, Fraccaro, Paolo, Lacoste, Alexandre, Khan, Salman
While numerous recent benchmarks focus on evaluating generic Vision-Language Models (VLMs), they fall short in addressing the unique demands of geospatial applications. Generic VLM benchmarks are not designed to handle the complexities of geospatial
Externí odkaz:
http://arxiv.org/abs/2411.19325
Accurate weather and climate modeling is critical for both scientific advancement and safeguarding communities against environmental risks. Traditional approaches rely heavily on Numerical Weather Prediction (NWP) models, which simulate energy and ma
Externí odkaz:
http://arxiv.org/abs/2409.07585
Autor:
Danish, Muhammad Sohail, Khan, Muhammad Haris, Munir, Muhammad Akhtar, Sarfraz, M. Saquib, Ali, Mohsen
In this work, we tackle the problem of domain generalization for object detection, specifically focusing on the scenario where only a single source domain is available. We propose an effective approach that involves two key steps: diversifying the so
Externí odkaz:
http://arxiv.org/abs/2405.14497
Deep learning based object detectors struggle generalizing to a new target domain bearing significant variations in object and background. Most current methods align domains by using image or instance-level adversarial feature alignment. This often s
Externí odkaz:
http://arxiv.org/abs/2311.04815
Albeit revealing impressive predictive performance for several computer vision tasks, deep neural networks (DNNs) are prone to making overconfident predictions. This limits the adoption and wider utilization of DNNs in many safety-critical applicatio
Externí odkaz:
http://arxiv.org/abs/2311.03570
Deep neural networks (DNNs) have enabled astounding progress in several vision-based problems. Despite showing high predictive accuracy, recently, several works have revealed that they tend to provide overconfident predictions and thus are poorly cal
Externí odkaz:
http://arxiv.org/abs/2303.14404
Autor:
Ahmad Warraich, Hafeez Sohaib1 sohaib135@gmail.com, Munir, Muhammad Irfan2, Azeem, Muhammad Farhan3, Khan, Aamir Imtiaz1, Anwar, Moin1, Shafiq, Muhammad Umair4
Publikováno v:
Professional Medical Journal. Dec2024, Vol. 31 Issue 12, p1724-1729. 6p.
Autor:
Iqbal, Zafar1 (AUTHOR) zafar@kfu.edu.sa, Munir, Muhammad2 (AUTHOR)
Publikováno v:
Scientific Reports. 10/5/2024, Vol. 14 Issue 1, p1-18. 18p.