Deep Learning Based Fish Species Recognition, Size Estimation, and Freshness Measurement

Project Member(s): Zhang, J., Wu, Q.

Funding or Partner Organisation: Food Agility CRC Limited (Food Agility CRC)
Food Agility CRC Limited (Food Agility CRC)

Start year: 2019

Summary: This project aims to address the need to recognize fish species more accurately in recorded databases, estimate fish size using mobile or suitable mounted cameras, and measure the freshness of fish according to its appearance.

Publications:

Wang, X, Yu, G, Liu, RP, Zhang, J, Wu, Q, Su, SW, He, Y, Zhang, Z, Yu, L, Liu, T, Zhang, W, Loneragan, P, Dutkiewicz, E, Poole, E & Paton, N 2022, 'Blockchain-Enabled Fish Provenance and Quality Tracking System', IEEE Internet of Things Journal, vol. 9, no. 11, pp. 8130-8142.
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Zhang, Z, Yu, L, Zhang, J & Wu, Q 1970, 'A Vision Based Fish Processing System', 2020 IEEE International Conference on Visual Communications and Image Processing (VCIP), 2020 IEEE International Conference on Visual Communications and Image Processing (VCIP), IEEE, Macau, China, pp. 1-1.
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FOR Codes: Computer Software and Services, Image Processing, Media services, Information systems, technologies and services

Acknowledgement of Country

UTS acknowledges the Gadigal people of the Eora Nation, the Boorooberongal people of the Dharug Nation, the Bidiagal people and the Gamaygal people, upon whose ancestral lands our university stands. We would also like to pay respect to the Elders both past and present, acknowledging them as the traditional custodians of knowledge for these lands.