Computer Vision Applications for Fisheries and Aquaculture

A special issue of Fishes (ISSN 2410-3888). This special issue belongs to the section "Fishery Facilities, Equipment, and Information Technology".

Deadline for manuscript submissions: 31 July 2026 | Viewed by 3

Special Issue Editors


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Guest Editor
College of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou 310058, China
Interests: fishery facilities; mechanical equipment; information technology; intelligent aquaculture; welfare aquaculture

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Co-Guest Editor
Information Technology Research Center, Beijing Academy of Agriculture and Forestry Science, Beijing 100097, China
Interests: fish behavior and intelligent fish feeding; the welfare of aquatic animals in aquaculture; artificial intelligence and IoT in aquaculture
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Guest Editor Assistant
Fishery Machinery and Instrument Research Institute, Chinese Academy of Fisheries Sciences, Shanghai, China
Interests: fish behavior analysis; computer vision

Special Issue Information

Dear Colleagues,

The fisheries and aquaculture sectors are undergoing a transformative shift towards precision management and sustainable practices, driven by technological innovation. Computer vision, as a core component of artificial intelligence, is rapidly emerging as a powerful tool to address long-standing challenges in these fields. This Special Issue aims to compile high-quality research and review articles that showcase the latest advancements and applications of computer vision across the entire aquatic food production chain.

The scope encompasses, but is not limited to, the following areas: automated biomass estimation, individual fish identification and tracking, behavior analysis for welfare and feeding optimization, species classification and sorting, early disease detection, underwater habitat and seabed monitoring, quality assessment of harvested aquatic products (e.g., freshness grading, defect detection), and the development of novel imaging systems (e.g., underwater, hyperspectral, low-cost) tailored for aquatic environments. We seek contributions that not only demonstrate technical excellence in algorithm development (deep learning, image processing) but also clearly articulate their practical impact on improving efficiency, sustainability, and profitability in aquaculture operations and wild fisheries management.

Prof. Dr. Zhangying Ye
Dr. Chao Zhou
Guest Editors

Dr. Weiqiang Ni
Guest Editor Assistant

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 250 words) can be sent to the Editorial Office for assessment.

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. Fishes 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 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.

Keywords

  • computer vision
  • aquaculture
  • fisheries management
  • underwater image analysis
  • fish behavior analysis
  • automated biomass estimation
  • species identification
  • quality inspection
  • precision aquaculture
  • deep learning

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Published Papers

This special issue is now open for submission.
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