In:
ICES Journal of Marine Science, Oxford University Press (OUP), Vol. 79, No. 2 ( 2022-03-10), p. 263-284
Abstract:
Automatic classification of different species of fish is important for the comprehension of marine ecology, fish behaviour analysis, aquaculture management, and fish health monitoring. In recent years, many automatic classification methods have been developed, among which machine vision-based classification methods are widely used with the advantages of being fast and non-destructive. In addition, the successful application of rapidly emerging deep learning techniques in machine vision has brought new opportunities for fish classification. This paper provides an overview of machine vision models applied in the field of fish classification, followed by a detailed discussion of specific applications of various classification methods. Furthermore, the challenges and future research directions in the field of fish classification are discussed. This paper would help researchers and practitioners to understand the applicability of machine vision in fish classification and encourage them to develop advanced algorithms and models to address the complex problems that exist in fish classification practice.
Type of Medium:
Online Resource
ISSN:
1054-3139
,
1095-9289
DOI:
10.1093/icesjms/fsab264
Language:
English
Publisher:
Oxford University Press (OUP)
Publication Date:
2022
detail.hit.zdb_id:
2463178-4
detail.hit.zdb_id:
1468003-8
detail.hit.zdb_id:
29056-7
SSG:
12
SSG:
21,3
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