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About Skip-YOLO: Domestic Garbage Detection Using Deep Learning Method in Complex Multi-Scenes
This document discusses a research paper that proposes a Skip-YOLO model for detecting domestic garbage in complex multi-scene images using deep learning. The model enlarges the receptive field using large convolution kernels to capture more image information. It then extracts high-dimensional feature maps of garbage using dense convolutional blocks. These feature maps are integrated and sent to the YOLO layer to predict the type and location of garbage. Experimental results show improved detection precision and recall over YOLOv3. The model successfully detects domestic garbage in complex scenes and alleviates overfitting compared to deep residual blocks.
Detailed Information
| Author: | ['R arnald'] |
|---|---|
| Publication Year: | 2022 |
| Pages: | 15 |
| Language: | English |
| Format: | |
| Price: | FREE |
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