TY - DATA T1 - Data underlying the publication: An integrated end-to-end deep neural network for automated detection of discarded fish species and their weight estimation. PY - 2024/06/11 AU - Maria Sokolova AU - Manuel Cordova AU - Henk Nap AU - Edwin van Helmond AU - Michiel Mans AU - Arjan Vroegop AU - Angelo Mencarelli AU - Gert Kootstra UR - DO - 10.4121/a6d5a40e-0358-47cf-9ec1-335df0e4a3c3.v2 KW - YOLOv5 KW - fisheries KW - weight estimation KW - occlusion KW - computer vision N2 -
The dataset contains images of the discarded fish on the conveyor belt and annotations. Annotations are prepared in YOLO format, i.e. separate text files, containing fish species label, object bounding box annotation, weight and occlusion level. Annotation per individual fish is written in a separate row of the file.
Additionally, we provide weight file (.pt) for the best performing Detection-Weight2 model.
ER -