Object detection (dangerous wildlife detection)
Wild animal attacks have cost hundreds of thousands human lives each year worldwide. With the rapid advancement of object detection algorithms, many practical use cases of object detection have been developed for the betterment of our lives. Therefore, this project proposes a real time animal det...
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| Format: | Final Year Project |
| Language: | English |
| Published: |
Nanyang Technological University
2023
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| Online Access: | https://hdl.handle.net/10356/166099 |
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| Institution: | Nanyang Technological University |
| Language: | English |
| Summary: | Wild animal attacks have cost hundreds of thousands human lives each year
worldwide. With the rapid advancement of object detection algorithms, many
practical use cases of object detection have been developed for the betterment of our
lives. Therefore, this project proposes a real time animal detection model to detect
and provide early warnings when encountering a dangerous animal in the wild.
In this project, we will determine a suitable model by evaluating 2 types of object
detection algorithms, One-stage detector algorithm YOLOv8, and Two-stage
detector algorithm Faster R-CNN based on the mean average precision (mAP) score
and inference speed. The chosen model will then be integrated to a simple program
to detect dangerous animals in real time. |
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