arXiv:2606. 04345v1 Announce Type: cross Abstract: This paper presents HYolo, an intelligent IoT-based object detection framework that integrates hypergraph learning into the YOLO architecture.
By Isha Abid, Fawad Khan, Muhammad Khuram Shahzad
arXiv:2409. 16808v3 Announce Type: replace-cross Abstract: Modern applications such as autonomous vehicles, intelligent surveillance, and smart city systems increasingly require object detection on resource-constrained edge devices.
By Daghash K. Alqahtani, Muhammad Aamir Cheema, Maria A. Rodriguez, Adel N. Toosi
arXiv:2602. 22794v2 Announce Type: replace Abstract: Internet of Things (IoT) networks face significant challenges such as limited communication bandwidth, constrained computational and energy resources, and highly dynamic wireless channel conditions.
By Soroosh Miri, Sepehr Abolhasani, Shahrokh Farahmand, S. Mohammad Razavizadeh, Jiguang He
arXiv:2607.17669v2 Announce Type: replace
Abstract: Drone-based object detection technology has advanced rapidly, becoming increasingly sophisticated and efficient. Recently, research trends have exp...
By Hyun-Ki Jung
arXiv:2607. 02981v1 Announce Type: cross Abstract: Recent advancements in the Internet of Things (IoT) emphasize the urgent need for advanced network security, as IoT networks feature dynamic topologies, imbalanced traffic, and complex attack patterns.
By Long Zhao, Shixun Ji, Bin Cheng, Bin He
arXiv:2609.24455v1 Announce Type: cross
Abstract: Intelligent transportation systems require Incremental Learning (IL) to continually improve their overall performance in dynamic environments. Howeve...
By Matthias Neuwirth-Trapp, Maarten Bieshaar, Danda Paudel, Konrad Schindler, Luc Van Gool, Christos Sakaridis