Mammal Classification Dataset

该数据集包含5个类别，共2500张哺乳动物图像（每个类别500张），以及10000个概念实例（每个类别2000个）。该数据集专为在CNN模型中进行透明度-可解释性实验而设计。规模上，它包含了2500张图像和10000个概念实例。任务是对哺乳动物图像进行分类。

This dataset consists of 5 categories, with 2,500 mammal images (500 per category) and 10,000 concept instances (2,000 per category). It is specifically designed for transparency and interpretability experiments using Convolutional Neural Network (CNN) models. The scale of this dataset includes the aforementioned 2,500 images and 10,000 concept instances, and its core task is to classify mammal images.