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20222025
most citedDeep reinforcement learning for machine scheduling: Methodology, the state-of-the-art, and future directions

49 citations · 215 across the 27 of their papers we have counts for

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7 papers · 1 filter

cs.CV2025

Object Recognition Datasets and Challenges: A Review

Aria Salari, Abtin Djavadifar, Xiangrui Liu +1

Object recognition is among the fundamental tasks in the computer vision applications, paving the path for all other image understanding operations. In every stage of progress in o…

cs.CV2024★ 2 cited

Ego-Motion Aware Target Prediction Module for Robust Multi-Object Tracking

Navid Mahdian, Mohammad Jani, Amir M. Soufi Enayati +1

Multi-object tracking (MOT) is a prominent task in computer vision with application in autonomous driving, responsible for the simultaneous tracking of multiple object trajectories…

cs.CV2023

Gap and Overlap Detection in Automated Fiber Placement

Assef Ghamisi, Homayoun Najjaran

The identification and correction of manufacturing defects, particularly gaps and overlaps, are crucial for ensuring high-quality composite parts produced through Automated Fiber P…

cs.CV2023★ 16 cited

Anomaly Detection in Automated Fibre Placement: Learning with Data Limitations

Assef Ghamisi, Todd Charter, Li Ji +3

Conventional defect detection systems in Automated Fibre Placement (AFP) typically rely on end-to-end supervised learning, necessitating a substantial number of labelled defective…

cs.CV2023★ 12 cited

Model Compression Methods for YOLOv5: A Review

Mohammad Jani, Jamil Fayyad, Younes Al-Younes +1

Over the past few years, extensive research has been devoted to enhancing YOLO object detectors. Since its introduction, eight major versions of YOLO have been introduced with the…

cs.CV2023★ 13 cited

Bag of Views: An Appearance-based Approach to Next-Best-View Planning for 3D Reconstruction

Sara Hatami Gazani, Matthew Tucsok, Iraj Mantegh +1

UAV-based intelligent data acquisition for 3D reconstruction and monitoring of infrastructure has experienced an increasing surge of interest due to recent advancements in image pr…

cs.CV2023

Object Semantics Give Us the Depth We Need: Multi-task Approach to Aerial Depth Completion

Sara Hatami Gazani, Fardad Dadboud, Miodrag Bolic +2

Depth completion and object detection are two crucial tasks often used for aerial 3D mapping, path planning, and collision avoidance of Uncrewed Aerial Vehicles (UAVs). Common solu…