Image Segmentation Techniques: Current Status and Future Directions (2nd Edition)

Dear Colleagues,

Image segmentation, as a fundamental and challenging task in many subjects such as image processing and computer vision, is of great importance but is constantly challenging to deliver. Briefly speaking, it is the process of assigning a label to every pixel in an image according to certain characteristics such as intensity, biometrics and semantics. It is generally a prerequisite and plays a key role in its ubiquitous practical applications, such as machine vision, medical imaging, detection, recognition, and autonomous driving. Researchers are increasing their efforts to develop new segmentation techniques based on, e.g., mathematical/statistical models, biometrics, and machine learning via deep neural networks to tackle existing and upcoming challenges.

This Special Issue aims to gather innovative research on image segmentation techniques, ranging from the current status to future directions, and from hand-crafted techniques to deep learning, etc. We also welcome submissions including, but not limited to, applications in digital imaging, medical imaging, object detection, and recognition tasks, among other related topics.

Dr. Xiaohao Cai
Prof. Dr. Gaohang Yu
Guest Editors

Manuscript Submission Information

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