Identification of Grouper Fish Types using Convolutional Neural Network Resnet-50 Algorithm
Year: 2025
Type: article
Abstract: Grouper is a type of fish that is popular with the public. It is necessary to identify the type of grouper fish based on color patterns with increase the epoch value to get the best accuracy. The purpose of the research is to predict the type of grouper. This research use CNN Resnet-50 algorithm. 30 data used. The accuracy of prediction is 75 % to predict the image groupers. In the grouper prediction process, the more we increase the epoch value, we will get the best accuracy value. Epoch is a factor that affects the time of training an AI model and affects the accuracy value of the AI model.
Source: JURNAL SISTEM INFORMASI BISNIS
Authors: Rini Nuraini, Wahyul Amien Syafei, Adi Wibowo, Indra Jaya
Institutions: Diponegoro University, Nasional University, IPB University
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W4411242576