地球资源数据云——数据资源详情

绵羊品种分类

发布时间：2026-03-17 15:34:09资源ID：2033809081633247233资源类型：免费

该数据集《Sheep Breed Classification》主要用于多分类任务，数据形态以图像为主，应用场景偏向农业场景。 题目说明：Four Variety of Sheep Breed Images from Australia 任务类型：图像多分类。 建议流程：先检查类别分布与脏样本，再用迁移学习（如 ResNet/EfficientNet）建立基线。 评估建议：使用分层切分或交叉验证，优先关注 F1、Recall、AUC 等分类指标。 可用文件：未检测到标准 CSV，可优先查看目录中的索引或说明文件。 Enough of dogs and cats!!! Enjoy this data to classify sheep into one of the four categories. This data is originally the efforts of Abu Jwade Sanabel et al. The team collected the data from a real farm in Australia. Further, this data was scraped from the web under the CC BY 4.0 license and presented here. Sheep from four sheep breeds were recorded while being drafted on the farm. Individual frames capturing sheep are grouped by breed. There is a main folder for aligned sheep images, inside which there is a folder for each of the four breeds' images. Could you train a classification model with an accuracy of more than 95%? If you intend to use this data please cite the following articles: 1. S. Abu Jwade, A. Guzzomi, and A. Mian, “On farm automatic sheep breed classification using deep learning,” Comput. Electron. Agric., vol. 167, no. June, pp. 1–13, 2019, doi: 10.1016/j.compag.2019.105055.

绵羊品种分类

摘要概览

该数据集《Sheep Breed Classification》主要用于多分类任务，数据形态以图像为主，应用场景偏向农业场景。 题目说明：Four Variety of Sheep Breed Images from Australia

任务类型：图像多分类。

建议流程：先检查类别分布与脏样本，再用迁移学习（如 ResNet/EfficientNet）建立基线。

评估建议：使用分层切分或交叉验证，优先关注 F1、Recall、AUC 等分类指标。

可用文件：未检测到标准 CSV，可优先查看目录中的索引或说明文件。

Enough of dogs and cats!!! Enjoy this data to classify sheep into one of the four categories. This data is originally the efforts of Abu Jwade Sanabel et al. The team collected the data from a real farm in Australia. Further, this data was scraped from the web under the CC BY 4.0 license and presented here.

Sheep from four sheep breeds were recorded while being drafted on the farm. Individual frames capturing sheep are grouped by breed. There is a main folder for aligned sheep images, inside which there is a folder for each of the four breeds' images.

Could you train a classification model with an accuracy of more than 95%?

If you intend to use this data please cite the following articles:

1. S. Abu Jwade, A. Guzzomi, and A. Mian, “On farm automatic sheep breed classification using deep learning,” Comput. Electron. Agric., vol. 167, no. June, pp. 1–13, 2019, doi: 10.1016/j.compag.2019.105055.