广东海洋大学章红鱼幼苗异常行为图像标注数据集

数据集是精细标注的章红鱼异常行为数据集。数据集核心在于系统化捕捉并标注了章红鱼在养殖环境中因温度变化表现的异常行为，包括缺氧行为和趴底行为。数据集共包含2401张章红鱼幼苗异常行为图像数据集及对应的标注文件，涵盖早中晚三个时间段光线条件的变化，通过学校自主研发的GAB-YOLO卷积神经网络模型，可用于集成化养殖环境下的章红鱼幼苗异常行为的识别，填补了章红鱼异常化行为研究的数据空白，为智能水产养殖提供了高效、低成本的解决方案。This is a finely annotated dataset focused on the abnormal behaviors of juvenile greater amberjack. The core of this dataset lies in systematically capturing and annotating the abnormal behaviors exhibited by juvenile greater amberjack in aquaculture environments induced by temperature fluctuations, including hypoxic behaviors and bottom-perching behaviors. The dataset comprises 2401 images of abnormal behaviors of juvenile greater amberjack along with their corresponding annotation files, covering variations in light conditions across three time periods: morning, midday, and evening. Utilizing the GAB-YOLO convolutional neural network independently developed by the university, this dataset can be applied to the identification of abnormal behaviors of juvenile greater amberjack in integrated aquaculture environments. It fills the data gap in research on abnormal behaviors of greater amberjack, providing an efficient and low-cost solution for intelligent aquaculture.