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pro vyhledávání: '"A Anwar Ali"'
Unmanned Surface Vehicles (USVs) have emerged as a major platform in maritime operations, capable of supporting a wide range of applications. USVs can help reduce labor costs, increase safety, save energy, and allow for difficult unmanned tasks in ha
Externí odkaz:
http://arxiv.org/abs/2412.01461
Recently, there has been growing interest in autonomous shipping due to its potential to improve maritime efficiency and safety. The use of advanced technologies, such as artificial intelligence, can address the current navigational and operational c
Externí odkaz:
http://arxiv.org/abs/2411.04915
Autor:
Wang, Xinran, Le, Qi, Ahmed, Ammar, Diao, Enmao, Zhou, Yi, Baracaldo, Nathalie, Ding, Jie, Anwar, Ali
Ensuring that generative AI systems align with human values is essential but challenging, especially when considering multiple human values and their potential trade-offs. Since human values can be personalized and dynamically change over time, the d
Externí odkaz:
http://arxiv.org/abs/2410.19198
This paper presents a comprehensive study on the scalability challenges and opportunities in quantum communication networks, with the goal of determining parameters that impact networks most as well as the trends that appear when scaling networks. We
Externí odkaz:
http://arxiv.org/abs/2409.08416
Autor:
Tang, Jiaxang, Fayyaz, Zeshan, Salahuddin, Mohammad A., Boutaba, Raouf, Zhang, Zhi-Li, Anwar, Ali
Federated Learning is a well-researched approach for collaboratively training machine learning models across decentralized data while preserving privacy. However, integrating Homomorphic Encryption to ensure data confidentiality introduces significan
Externí odkaz:
http://arxiv.org/abs/2409.07631
Personalized Federated Learning (pFL) holds immense promise for tailoring machine learning models to individual users while preserving data privacy. However, achieving optimal performance in pFL often requires a careful balancing act between memory o
Externí odkaz:
http://arxiv.org/abs/2409.06805
Federated Learning (FL) is a collaborative machine learning framework that allows multiple users to train models utilizing their local data in a distributed manner. However, considerable statistical heterogeneity in local data across devices often le
Externí odkaz:
http://arxiv.org/abs/2409.04986
Maintaining roads is crucial to economic growth and citizen well-being because roads are a vital means of transportation. In various countries, the inspection of road surfaces is still done manually, however, to automate it, research interest is now
Externí odkaz:
http://arxiv.org/abs/2407.14418
Publikováno v:
27th IEEE International Conference on Intelligent Transportation Systems 2024
As the popularity of autonomous vehicles has grown, many standards and regulators, such as ISO, NHTSA, and Euro NCAP, require safety validation to ensure a sufficient level of safety before deploying them in the real world. Manufacturers gather a lar
Externí odkaz:
http://arxiv.org/abs/2407.12065
Roads are an essential mode of transportation, and maintaining them is critical to economic growth and citizen well-being. With the continued advancement of AI, road surface inspection based on camera images has recently been extensively researched a
Externí odkaz:
http://arxiv.org/abs/2407.10197