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Classification of Salmon Freshness In Situ Using Convolutional Neural Network

Year: 2025

Type: conference-paper

Abstract: Fish is an important food resource, an economic contributor, and a staple food for Filipinos. For the safety and satisfaction of consumers, fish freshness must be determined. Using the convolutional neural network (CNN) algorithm, we determined salmon fillet freshness in this study. In total, 7000 images were used for training and 40 for testing the CNN model. The deep learning technique, specifically ResNet50 architecture, was used with Raspberry Pi 4B, and Raspberry Pi camera V2 was employed to take images of fish. The model showed a 92.5% accuracy, highlighting the CNN model’s accurate evaluation of seafood quality.

Source: IEEE Eurasia Conference on IOT, Communication and Engineering (ECICE)

DOI: 10.3390/engproc2025092012

Authors: Juan Miguel L. Valeriano, Carlos C. Hortinela

Institution: Mapúa University

Language: English

Topic: Advanced Neural Network Applications

Subfield: Computer Vision and Pattern Recognition

Field: Computer Science

Domain: Physical Sciences

SDG: Zero hunger

Open Access status: hybrid

OpenAlex ID: W4409698753

FWCI: 0.857

Cites: 17

Cited by: 1

Related to: 10