Zobrazeno 1 - 10
of 3 300
pro vyhledávání: '"AHMED, MUHAMMAD"'
In autonomous robotics, a significant challenge involves devising robust solutions for Active Collaborative SLAM (AC-SLAM). This process requires multiple robots to cooperatively explore and map an unknown environment by intelligently coordinating th
Externí odkaz:
http://arxiv.org/abs/2407.05453
Autor:
Shao, Wei, Zhu, Rongyi, Yang, Cai, Thapa, Chandra, Ahmed, Muhammad Ejaz, Camtepe, Seyit, Zhang, Rui, Kim, DuYong, Menouar, Hamid, Salim, Flora D.
Spatiotemporal data is prevalent in a wide range of edge devices, such as those used in personal communication and financial transactions. Recent advancements have sparked a growing interest in integrating spatiotemporal analysis with large-scale lan
Externí odkaz:
http://arxiv.org/abs/2406.03404
Autor:
Klimov, Egor, Ahmed, Muhammad Umair, Sviridov, Nikolai, Derakhshanfar, Pouria, Tüzün, Eray, Kovalenko, Vladimir
Publikováno v:
2023 38th IEEE/ACM International Conference on Automated Software Engineering (ASE), Luxembourg, Luxembourg, 2023 pp. 2018-2021
Bus factor (BF) is a metric that tracks knowledge distribution in a project. It is the minimal number of engineers that have to leave for a project to stall. Despite the fact that there are several algorithms for calculating the bus factor, only a fe
Externí odkaz:
http://arxiv.org/abs/2403.08038
In this article, we present an efficient multi-robot active SLAM framework that involves a frontier-sharing method for maximum exploration of an unknown environment. It encourages the robots to spread into the environment while weighting the goal fro
Externí odkaz:
http://arxiv.org/abs/2310.06160
Autor:
Ahmed, Muhammad Farhan, Maragliano, Matteo, FremontCarmine, Vincent, Recchiuto, Tommaso, Sgorbissa, Antonio
In autonomous robotics, a critical challenge lies in developing robust solutions for Active Collaborative SLAM, wherein multiple robots collaboratively explore and map an unknown environment while intelligently coordinating their movements and sensor
Externí odkaz:
http://arxiv.org/abs/2310.01967
Publikováno v:
Conference: 2023 IEEE International Conference on Service Operations and Logistics, and Informatics (SOLI)
In this article we present a utility function for Active SLAM (A-SLAM) which utilizes map entropy along with D-Optimality criterion metrices for weighting goal frontier candidates. We propose a utility function for frontier goal selection that exploi
Externí odkaz:
http://arxiv.org/abs/2309.16490
Kernel fuzzing is important for finding critical kernel vulnerabilities. Close-source (e.g., Windows) operating system kernel fuzzing is even more challenging due to the lack of source code. Existing approaches fuzz the kernel by modeling syscall seq
Externí odkaz:
http://arxiv.org/abs/2308.04115
Autor:
Liu, Zian, Zhang, Zhi, Ma, Siqi, Liu, Dongxi, Zhang, Jun, Chen, Chao, Liu, Shigang, Ahmed, Muhammad Ejaz, Xiang, Yang
Binary similarity detection is a critical technique that has been applied in many real-world scenarios where source code is not available, e.g., bug search, malware analysis, and code plagiarism detection. Existing works are ineffective in detecting
Externí odkaz:
http://arxiv.org/abs/2308.01463
Autor:
Tran, Quoc-Huy, Mehmood, Ahmed, Ahmed, Muhammad, Naufil, Muhammad, Zafar, Anas, Konin, Andrey, Zia, M. Zeeshan
This paper presents an unsupervised transformer-based framework for temporal activity segmentation which leverages not only frame-level cues but also segment-level cues. This is in contrast with previous methods which often rely on frame-level inform
Externí odkaz:
http://arxiv.org/abs/2305.19478
Autor:
Tran, Quoc-Huy, Ahmed, Muhammad, Popattia, Murad, Ahmed, M. Hassan, Konin, Andrey, Zia, M. Zeeshan
This paper presents a self-supervised temporal video alignment framework which is useful for several fine-grained human activity understanding applications. In contrast with the state-of-the-art method of CASA, where sequences of 3D skeleton coordina
Externí odkaz:
http://arxiv.org/abs/2305.19480