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Symmetry
Special Issues
Symmetry and Its Applications in Computer Vision
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Symmetry and Its Applications in Computer Vision

A special issue of Symmetry (ISSN 2073-8994). This special issue belongs to the section "Computer".

Deadline for manuscript submissions: 31 October 2025 | Viewed by 1024

Special Issue Editors

Dr. Yunyi Yan

E-Mail Website
Guest Editor
Associate professor. School of Aerospace Science and Technology, Xidian University, Xi’an 710126, China
Interests: modeling and optimization design of complex system; intelligent algorithms in computer vision; situation awareness based on image understanding
Prof. Dr. Junxuan Wang

E-Mail Website
Guest Editor
School of Communications and Information Engineering, Xi'an University of Posts and Telecommunications, Xi'an, China
Interests: Signal processing; Broadband wireless communication; Internet of Things
Dr. Lu Zhao

E-Mail Website
Guest Editor
Institute for Neuroimaging and Informatics, University of Southern California, Los Angeles, CA, USA
Interests: computational neuroimaging analysis and the application to studies of neuroanatomy and brain connectivity networks and their relationship to development, aging and pathological conditions

Special Issue Information

Dear Colleagues,

Symmetry and its relative extension has driven great innovations in sciences including physics, chemical, and mathematics. In fact, the importance of symmetry is undeniable in computer vision as it plays a crucial role in various theories and applications from signal processing and object recognition to scene understanding.

This Special Issue aims to bring together a collection of at least 10 articles that explore the scientific background, theoretical foundations, and practical applications of symmetry or asymmetry in computer vision. The Special Issue may be printed in book form if the minimum number of articles is reached. And articles submitted to this Special Issue will be published by the journal within 5 or less days on average if it is accepted after reviewing is finished.

We invite original research articles and reviews that address, but are not limited to, the followings:

  • Theoretical foundations of symmetry or asymmetry in computer vision;
  • Symmetry-based algorithms for object recognition and scene analysis;
  • Applications of symmetry in medical image processing;
  • Symmetry and/or asymmetry study of neuroscience cases;
  • Symmetry computational intelligence in signal and multimedia analysis;
  • Signal analysis theory applications in symmetry detection;
  • Optimization techniques involving symmetry architecture;
  • Large models design and application inspired by symmetry concept;
  • Novel methods in computer vision originating from other fields.

Please submit your manuscript via the journal's online submission system, ensuring that you select the appropriate article type for the Special Issue. All submissions will undergo rigorous peer review, and authors will be notified of the outcome as soon as possible.

We look forward to receiving your contributions and to showcasing the latest research in symmetry and its applications in computer vision. For any inquiries regarding the Special Issue, please do not hesitate to contact Dr. Yunyi Yan directly.

Dr. Yunyi Yan
Prof. Dr. Junxuan Wang
Dr. Lu Zhao
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. Symmetry is an international peer-reviewed open access monthly 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 2400 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.

Keywords

  • symmetry and asymmetry
  • computer vision
  • artificial intelligence and neuroscience
  • signal and image processing or analysis
  • large model optimization and application

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Further information on MDPI's Special Issue policies can be found here.

Published Papers (2 papers)

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Research

21 pages, 2471 KiB  
Article
Attention-Based Mask R-CNN Enhancement for Infrared Image Target Segmentation
by Liang Wang and Kan Ren
Symmetry 2025, 17(7), 1099; https://doi.org/10.3390/sym17071099 - 9 Jul 2025
Viewed by 281
Abstract
Image segmentation is an important method in the field of image processing, while infrared (IR) image segmentation is one of the challenges in this field due to the unique characteristics of IR data. Infrared imaging utilizes the infrared radiation emitted by objects to [...] Read more.
Image segmentation is an important method in the field of image processing, while infrared (IR) image segmentation is one of the challenges in this field due to the unique characteristics of IR data. Infrared imaging utilizes the infrared radiation emitted by objects to produce images, which can supplement the performance of visible-light images under adverse lighting conditions to some extent. However, the low spatial resolution and limited texture details in IR images hinder the achievement of high-precision segmentation. To address these issues, an attention mechanism based on symmetrical cross-channel interaction—motivated by symmetry principles in computer vision—was integrated into a Mask Region-Based Convolutional Neural Network (Mask R-CNN) framework. A Bottleneck-enhanced Squeeze-and-Attention (BNSA) module was incorporated into the backbone network, and novel loss functions were designed for both the bounding box (Bbox) regression and mask prediction branches to enhance segmentation performance. Furthermore, a dedicated infrared image dataset was constructed to validate the proposed method. The experimental results demonstrate that the optimized model achieves higher segmentation accuracy and better segmentation performance compared to the original network and other mainstream segmentation models on our dataset, demonstrating how symmetrical design principles can effectively improve complex vision tasks. Full article
(This article belongs to the Special Issue Symmetry and Its Applications in Computer Vision)
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24 pages, 9307 KiB  
Article
DASS-YOLO: Improved YOLOv7-Tiny with Attention-Guided Shape Awareness and DySnakeConv for Spray Code Defect Detection
by Yixuan Shi, Shiling Zheng, Meiyue Bian, Xia Zhang and Lishan Yang
Symmetry 2025, 17(6), 906; https://doi.org/10.3390/sym17060906 - 8 Jun 2025
Viewed by 458
Abstract
To address the challenges of detecting spray code defects caused by complex morphological variations and the discrete characterization of dot-matrix spray codes, an improved YOLOv7-tiny algorithm named DASS-YOLO is proposed. Firstly, the DySnakeConv module is employed in Backbone–Neck cross-layer connections. With a dynamic [...] Read more.
To address the challenges of detecting spray code defects caused by complex morphological variations and the discrete characterization of dot-matrix spray codes, an improved YOLOv7-tiny algorithm named DASS-YOLO is proposed. Firstly, the DySnakeConv module is employed in Backbone–Neck cross-layer connections. With a dynamic structure and adaptive learning, it can capture the complex morphological features of spray codes. Secondly, we proposed an Attention-guided Shape Enhancement Module with CAA (ASEM-CAA), which adopts a symmetrical dual-branch structure to facilitate bidirectional interaction between local and global features, enabling precise prediction of the overall spray code shape. It also reduces feature discontinuity in dot-matrix codes, ensuring a more coherent representation. Furthermore, Slim-neck, which is famous for its more lightweight structure, is adopted in the Neck to reduce model complexity while maintaining accuracy. Finally, Shape-IoU is applied to improve the accuracy of the bounding box regression. Experiments show that DASS-YOLO improves the detection accuracy by 1.9%. Additionally, for small defects such as incomplete code and code spot, the method achieves better accuracy improvements of 8.7% and 2.1%, respectively. Full article
(This article belongs to the Special Issue Symmetry and Its Applications in Computer Vision)
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