Image-Based Object Detection

Dear Colleagues,

Image-based object detection, a cornerstone of computer vision, enables machines to identify and localize objects in visual data, underpinning advancements in autonomous driving, surveillance, medical imaging, and robotics. In recent years, transformative progress, driven by deep learning, has been made, from convolutional neural networks (CNNs) to transformer-based architectures, yet critical challenges persist, such as handling occlusions, small/low-light objects, domain shifts, and real-time efficiency in dynamic environments.

This Special Issue aims to showcase cutting-edge research addressing these hurdles. We welcome the submission of original contributions focused on novel algorithms, benchmark datasets, robustness enhancements (e.g., against adversarial attacks), and cross-domain applications. By integrating theoretical innovations with practical solutions, this Special Issue seeks to accelerate the translation of image-based detection technologies to real-world impacts.

Dr. Jinxing Li
Guest Editor

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