NorFisk Dataset

Long-term autonomous monitoring of wild fish populations surrounding fish farms can contribute to a better understanding of interactions between wild and farmed fish, which can have wide-ranging implications for disease transmission, stress in farmed fish, wild fish behavior and nutritional status, etc. The ability to monitor the presence of wild fish and its variability with time and space will improve our understanding of the dynamics of such interactions and the implications that follow. Many efforts are underway to recognize fish species using artificial intelligence. However there are not many image datasets publicly available to train these neural networks, and even fewer that include species that are relevant for the aquaculture sector. Here we present a public dataset of annotated images for fish species recognition with deep learning. The dataset contains 9487 annotated images of farmed salmonids and 3027 annotated images of saithe and it is expected to grow in the near future. This dataset was the result of processing nearly 50 hours of video footage taken inside and outside cages from several fish farms in Norway. The footage was processed with a semi-automatic system to create large image datasets of fish under water. The system combines techniques of image processing with deep neural networks in an iterative process to extract, label, and annotate images from video sources. The details of the system are described in a journal paper that is currently under review. This information will be updated when the paper is published.

对渔场周边野生鱼类种群开展长期自主监测，有助于深化对野生与养殖鱼类相互作用的认知，而此类相互作用对疾病传播、养殖鱼类应激反应、野生鱼类行为模式及营养状态等诸多方面均具有广泛影响。掌握野生鱼类的存在情况及其时空分布变化规律，将有助于我们进一步明晰这类相互作用的动态过程与后续影响。当前已有众多研究致力于利用人工智能（Artificial Intelligence）实现鱼类物种识别。然而，目前可用于训练此类神经网络的公开鱼类图像数据集仍较为稀缺，且其中涵盖水产养殖相关物种的数据集更是凤毛麟角。为此，我们推出一款面向深度学习鱼类物种识别任务的带标注图像公开数据集。该数据集包含9487张养殖鲑科鱼类（salmonids）的标注图像，以及3027张绿青鳕（saithe）的标注图像，并预计在未来进一步扩充规模。本数据集源自对挪威多家渔场网箱内外采集的近50小时视频素材的处理工作。研究团队采用半自动系统对这些视频素材进行处理，以生成水下鱼类的大规模图像数据集。该系统将图像处理技术与深度神经网络相结合，通过迭代流程从视频素材中提取目标、标记类别并完成图像标注。该系统的详细技术细节已撰写为论文并投稿至学术期刊，目前处于审稿阶段；待论文正式发表后，本数据集的相关信息将进行更新完善。

搜集汇总

背景与挑战

背景概述

NorFisk Dataset是一个用于鱼类物种识别的公开数据集，包含12,514张标注图像（9487张养殖鲑鱼和3027张鳕鱼），来源于挪威渔场的水下视频监控。该数据集专为深度学习算法训练设计，重点关注水产养殖领域的野生与养殖鱼类交互研究。