Guest Editors
Prof. Taufiq Asyhari, Data Science and Information Engineering, Monash University, Indonesia, Bumi Serpong Damai, P2T PT, Indonesia
Dr. Sarwar Jahan, Department of Computer Science and Engineering, East West University, Dhaka, 1212, Bangladesh
Dr. Md Shantanu Islam, University of Wales Trinity Saint David, London, SA31 3EP, United Kingdom
Dr. Erza Aminanto, Cyber Security, Monash University, Indonesia, Bumi Serpong Damai, P2T PT, Indonesia
Summary
Recent advancements in computer vision and image processing have significantly enhanced object detection technologies, which are crucial for a wide range of applications such as autonomous driving, medical imaging, surveillance, and augmented reality. Object detection focuses on identifying and localizing objects within images, with the primary metrics being accuracy and speed. The rapid development of deep learning has led to remarkable improvements in these metrics, making object detection more efficient and reliable. This progress has enabled new applications and improved existing ones, making it a research hotspot.
This special issue aims to explore the latest trends in object detection, presenting cutting-edge research, methodologies, and technologies. By providing a platform for researchers and practitioners to share their insights and solutions, this issue seeks to provide a deeper understanding of current challenges and drive further advancements in object detection technology and its application in areas such as such as autonomous vehicles, robot vision, video surveillance.
Scope:
This special issue will cover a wide range of topics related to object detection, including but not limited to:
· Novel algorithms and models for object detection
· Deep learning applications in object detection
· Real-time object detection techniques
· Object detection in autonomous vehicles
· Medical imaging and diagnostics using object detection
· Integration of object detection with augmented reality
· Performance optimization of object detection systems
· Evaluation and benchmarking of object detection models
· Transfer learning and domain adaptation in object detection
· Object detection in low-light and adverse conditions
· Small object detection and handling occlusions
· Federated learning approaches for decentralized object detection
· 3D object detection and scene understanding
Objectives:
The main objectives of this special issue are to:
· Explore innovative techniques and tools that enhance the accuracy and efficiency of object detection systems.
· Discuss challenges and solutions related to the deployment of object detection in various environments.
· Foster discussions on the integration of object detection with emerging technologies.
Provide insights into the future direction of object detection research and development.
Keywords
Object Detection
Computer Vision
Deep Learning
Real-time Detection
Autonomous Vehicles
Medical Imaging
Augmented Reality
Performance Optimization
Benchmarking
Transfer Learning
Domain Adaptation
Low-light Detection
Small Object Detection
Federated Learning
3D Object Detection
Scene Understanding
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