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About A Survey On Deep Learning-Based Fine-Grained Object Classification and Semantic Segmentation
This document surveys deep learning approaches for fine-grained object classification and semantic segmentation. It reviews four types of approaches for fine-grained classification: general CNNs, part detection based, ensemble of networks based, and visual attention based. It also covers region proposal based and fully convolutional network based approaches for semantic segmentation. The document introduces concepts like CNNs, RNNs, backpropagation, and reinforcement learning and how they apply to these tasks.
Detailed Information
| Author: | ['Anonymous kIAESXSk'] |
|---|---|
| Publication Year: | 2018 |
| Pages: | 17 |
| Language: | English |
| Format: | |
| Price: | FREE |
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