Deep Learning in Image Analysis and Pattern Recognition, 2nd Edition

Dear Colleagues,

In the past decade, deep learning has demonstrated state-of-the-art performances in many image processing tasks, such as image classification, object detection, object tracking, image segmentation, etc. Despite remarkable deep learning-related achievements in computer vision, many challenging tasks and scenarios that require novel methods and theories remain. For example, lightweight object detection is required in many applications, such as autonomous driving scenarios; however, the discrepancy between the speed of a machine and human eyes remains large. Fine-grained or small-object detection is another area that has seen improvement. Weakly supervised object classification or detection is an important problem since the annotation process is time-consuming, expensive and inefficient. In addition, although deep learning achievements in computer vision have been successfully applied to many areas, greater efforts should be made to ensure that this technology can better serve humans in the future.

This Special Issue requests papers detailing new advances in deep learning methods or applications in image analysis and pattern recognition. Topics of interest include, but are not limited to, the following:

• Image classification;
• Object detection;
• Object tracking;
• Image segmentation;
• Convolutional neural networks;
• Diffusion model;
• Image captioning;
• Image clustering;
• Representation learning for images;
• Medical image processing;
• Remote sensing image processing;
• 3D image building.

Dr. Xianzhi Wang
Dr. Guoqing Chao
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Machine Learning and Knowledge Extraction is an international peer-reviewed open access quarterly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

• machine learning
• deep learning
• image analysis
• pattern recognition