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About Animal Classification
Deep learning neural networks were trained to automatically identify, count, and describe 48 animal species from 3.2 million images in the Snapshot Serengeti camera trap dataset. The neural networks identified animals with over 93.8% accuracy, and could automate labeling of 99.3% of images while maintaining 96.6% accuracy, equivalent to human volunteers. This automation could save over 17,000 hours of human labeling effort and unlock valuable ecological data for conservation.
Detailed Information
| Author: | ['Aadarsh Ramakrishnan'] |
|---|---|
| Publication Year: | 2019 |
| Pages: | 17 |
| Language: | English |
| Format: | |
| Price: | FREE |
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