Traditional technique application v/s YOLOv5 model for marine underwater objects detection by computer vision method
Journal: BIO Web of Conferences
Year: 2024

The paper compares the effectiveness of two methods application for detecting and recognizing micro-objects in an aqua environment on the example of plankton using neural networks and various technologies and developed in different programming languages. At first the traditional detection method was investigated and applied based on the extraction of Gabor and multilayer perceptron features, realized in MATrixLABoratory (MATLAB) language. Secondly, YOLOv5 (an acronym for ‘You only look once’), a