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Electronics
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Deep Learning for Image Analysis and Image Processing
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Deep Learning for Image Analysis and Image Processing

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Computer Science & Engineering".

Deadline for manuscript submissions: closed (15 November 2023) | Viewed by 1113

Special Issue Editor

Prof. Dr. Wei Qian

E-Mail Website
Guest Editor
1. College of Medicine and Biological Information Engineering, Northeastern University, Shenyang 110169, China
2. Department of Electrical and Computer Engineering, University of Texas, EI Paso, TX 79968, USA
Interests: medical imaging informatics; telemedicine; computerized biomedical imaging and molecular imaging biomarker analysis
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

This Special Issue seeks the latest fundamental advances in addressing the challenges of medical Artificial Intelligence. Specifically, this issue will explore the challenges faced by practical applications and propose feasible solutions through advanced deep learning and big data technologies. Both application and methodological research studies are welcome. The current leading topics include but are not limited to:

  • AI-based clinical decision making;
  • Biomedical information processing;
  • Computational intelligence in bio- and clinical medicine;
  • Computer-aided diagnosis model;
  • Data analytics and mining for biomedical decision support;
  • Data science theory, methodologies, and techniques;
  • Healthcare application and big data analysis;
  • Intelligent and process-aware information systems in healthcare and medicine;
  • Intelligent detection systems;
  • Intelligent devices and instruments;
  • Machine learning theory, methodology, and algorithms;
  • Medical knowledge engineering;
  • Natural language processing in medicine;
  • New computational platforms and models for biomedicine;
  • Sensor fusion of biomedical data.

Prof. Dr. Wei Qian
Guest Editor

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. Electronics 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 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

  • image analysis
  • image processing
  • data analysis
  • artificial intelligence

Published Papers (1 paper)

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Research

12 pages, 1196 KiB  
Article
DSA: Deformable Segmentation Attention for Multi-Scale Fisheye Image Segmentation
by Junzhe Jiang, Cheng Xu, Hongzhe Liu, Ying Fu and Muwei Jian
Electronics 2023, 12(19), 4059; https://doi.org/10.3390/electronics12194059 - 27 Sep 2023
Viewed by 757
Abstract
With a larger field of view (FOV) than ordinary images, fisheye images are becoming mainstream in the field of autonomous driving. However, the severe distortion problem of fisheye images also limits its application. The performance of neural networks designed for narrow FOV images [...] Read more.
With a larger field of view (FOV) than ordinary images, fisheye images are becoming mainstream in the field of autonomous driving. However, the severe distortion problem of fisheye images also limits its application. The performance of neural networks designed for narrow FOV images degrades drastically for fisheye images, and the use of large composite models can improve the performance, but it brings huge time overhead and hardware costs. Therefore, we decided to balance real time and accuracy by designing the deformable segmentation attention(DSA) module, a generalpurpose architecture based on a deformable attention mechanism and a spatial pyramid architecture. The deformable mechanism serves to accurately extract feature information from fisheye images, together with attention to learn the global context and the spatial pyramid structure to balance multiscale feature information, thus improving the perception of fisheye images by traditional networks without increasing the amount of excessive computation. Lightweight networks such as SegNeXt equipped with the DSA module enable effective and rapid multi-scale segmentation of fisheye images in complex scenes. Our architecture achieves outstanding results on the WoodScape dataset, while our ablation experiments demonstrate the effectiveness of various parts of the architecture. Full article
(This article belongs to the Special Issue Deep Learning for Image Analysis and Image Processing)
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