iWildCam 2019 Challenge Dataset
收藏arXiv2019-07-16 更新2024-08-06 收录
下载链接：
http://arxiv.org/abs/1907.07617v1
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资源简介：
iWildCam 2019 Challenge Dataset是由加州理工学院和微软AI for Earth合作创建的，旨在通过自动化的图像识别技术解决野生动物监测中的物种分类问题。该数据集包含292,732张来自美国西南部的训练图像和153,730张来自美国西北部的测试图像，涵盖多种动物类别。数据集的创建过程涉及从实际的野生动物监测中收集图像，并通过专家生物学家进行标注。该数据集主要应用于研究生物多样性、动物种群密度和行为模式，以解决全球范围内的野生动物保护和生态系统管理问题。
The iWildCam 2019 Challenge Dataset was developed in collaboration between the California Institute of Technology and Microsoft AI for Earth, with the core objective of addressing species classification tasks in wildlife monitoring through automated image recognition technologies. This dataset contains 292,732 training images collected from the southwestern United States and 153,730 test images sourced from the northwestern United States, covering a wide variety of animal taxa. The development process of this dataset involved gathering images from real-world wildlife monitoring projects and annotating them with the assistance of professional biologists. It is primarily applied to research on biodiversity, animal population density and behavioral patterns, so as to tackle global challenges in wildlife conservation and ecosystem management.
提供机构：
加州理工学院
创建时间：
2019-07-16
