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About Holistically-Nested Edge Detection
This document describes a new edge detection algorithm called holistically-nested edge detection (HED). HED uses a deep learning model with fully convolutional neural networks and deeply-supervised nets to perform image-to-image prediction of edges. It automatically learns hierarchical representations from images guided by deep supervision on intermediate responses. Evaluation on standard datasets shows HED achieves state-of-the-art performance for edge detection while being faster than other CNN-based methods.
Detailed Information
| Author: | ['hello123'] |
|---|---|
| Publication Year: | 2016 |
| Pages: | 10 |
| Language: | English |
| Format: | |
| Price: | FREE |
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