Mathematical Methods in Pattern Recognition and Image Analysis

Dear Colleagues,

Pattern recognition involves processing and analyzing various forms of information that characterizes phenomena in order to describe, identify, classify, and explain them. This area constitutes an important part of information science and artificial intelligence. Deep learning is the ruling approach in the field of pattern recognition and has been responsible for achieving breakthroughs in the field. However, for advanced perception, such as more complex reasoning processes across modalities or tasks or semantic-based applications (answering questions, human-computer interactions, autonomous driving decisions, etc.), some progress has been achieved. However, its implementation has not been improved upon until today. Therefore, combining mathematical methods for pattern recognition and comprehension and then using the results for decision planning is a promising direction requiring intensive future research.

This Special Issue accepts high-quality, original research papers and reviews describing breakthroughs in pattern recognition through novel mathematical theories or methods, as well as those using new methods to obtain better practical applications. Papers detailing interesting/significant new applications of machine learning, deep learning, and artificial intelligence are also welcome. Potential topics include, but are not limited to, the following:

• Pattern recognition and its application;
• Statistical methods in machine learning, deep learning, and artificial intelligence;
• Natural language processing (machine translation, human-computer interaction, speech recognition, text matching, text generation, text classification, sequence labeling, image caption, sentiment analysis, etc.);
• Computer vision and robot vision (feature extraction, object tracking, object detection, visual saliency detection, facial expression recognition, face recognition, fingerprint recognition, palmprint recognition, annotation, segmentation, classification, retrieval, etc.);
• Robotics and robotic systems (human-robot interaction, task planning, path planning, SLAM, multisensor data fusion, robot system modeling, multirobot systems, fault detection, self-calibration and self-repair for robots, robot learning and adaptation, humanoids, industrial robotics, etc.);
• Multimedia information processing and analysis (image/video transform, filtering, denoising, compression coding, deblocking, deblurring, dehazing, enhancement, restoration and reconstruction, inpainting, registration and fusion, interpolation, demosaicking, super-resolution, motion estimation, motion compensation, quality assessment, mathematical morphology, etc.);
• Multimedia information security (information hiding, forensics, digital watermarking, forgery detection, steganography and steganalysis, deepfake, face spoofing detection, etc.);
• Artificial intelligence security (adversarial example, model protection, privacy protection, data poisoning, backdoor attack and defense, etc.);
• Cyberspace security (cryptography and applications, big data security, advanced computer security in the context of big data, public opinion analysis, etc.);
• Wireless communications and networks (reconfigurable intelligence surface (RIS), dense heterogeneous network, nonorthogonal multiple access (NOMA), deep learning-based end-to-end wireless communication, terahertz (THz) spectrum, millimeter wave communication, air-ground integrated communication, edge computing, mobile cloud computing, cooperative communication, massive MIMO, full-spectrum communication, channel coding, channel estimation, internet security, IoT, wireless sensor networks, etc.).

Prof. Dr. Pierre Gouton
Prof. Dr. Sebti Foufou
Dr. Ludovic Journaux
Dr. Amadou Tidjani Sanda Mahama
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. Mathematics is an international peer-reviewed open access semimonthly 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 2600 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.

• mathematical methods
• pattern recognition
• image analysis
• image processing
• data analysis
• classification
• segmentation
• statistical modeling
• signal processing
• character recognition
• face recognition
• speech recognition
• machine learning
• artificial intelligence
• computer vision
• high-dimensional data analysis
• real-time processing
• time-series analysis