Low-Shot Wall Defect Detection for Autonomous Decoration Robots Using Deep Reinforcement Learning
Wall defect detection is an important function for autonomous decoration robots. Object detection methods based on deep neural networks require a large number of images with the handcrafted bounding box for training. Nonetheless, building large datasets manually is impractical, which is time-consumi...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2020-01-01
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| Series: | Journal of Robotics |
| Online Access: | http://dx.doi.org/10.1155/2020/8866406 |
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