Scientists develop computer vision framework to track animals in the wild without markers

Researchers from the Cluster of Excellence Collective Behavior have developed a computer vision framework for posture estimation and identity tracking that they can use in indoor environments as well as in the wild. This is an important step toward the markerless tracking of animals in the wild using computer vision and machine learning. Researchers from the Cluster of Excellence Collective Behavior have developed a computer vision framework for posture estimation and identity tracking that they can use in indoor environments as well as in the wild. This is an important step toward the markerless tracking of animals in the wild using computer vision and machine learning. Plants & Animals Biotechnology Phys.org – latest science and technology news stories

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