FishNet: Deep Neural Networks for Low-Cost Fish Stock Estimation

arXiv:2403.10916v1 Announce Type: new
Abstract: Fish stock assessment often involves manual fish counting by taxonomy specialists, which is both time-consuming and costly. We propose an automated computer vision system that performs both taxonomic classification and fish size estimation from images taken with a low-cost digital camera. The system first performs object detection and segmentation using a Mask R-CNN to identify individual fish from images containing multiple fish, possibly consisting of different species. Then each fish species is classified and the …

abstract arxiv assessment automated classification computer computer vision cost cs.cv digital econ.gn fish images low networks neural networks object q-fin.ec stock taxonomy type vision