【圖像分割論文閱讀】Efficient ConvNet for Real-time Semantic Segmentation
文章由西班牙阿爾拉卡大學電子系Eduardo Romera等人完成。發表在2017 IEEE Intelligent Vehicles Symposium (IV). 論文地址:Efficient ConvNet for Real-time Semantic Segmentation 背景 自動駕駛是極具挑戰性的任務，需要在感知任務中採用複雜的解決方案，如識別道路、交通燈、車輛行人等。但是當前的模
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相關文章
- 1. 【圖像分割論文閱讀】LinkNet: Exploiting Encoder Representations for Efficient Semantic Segmentation
- 2. 論文閱讀（詳細）：ERFNet: Efficient Residual Factorized ConvNet for Real-Time Semantic Segmentation
- 3. 【圖像分割論文閱讀】DenseASPP for Semantic Segmentation in Street Scenes
- 4. 【圖像分割論文閱讀】RefineNet: Multi-Path Refinement Networks for High-Resolution Semantic Segmentation
- 5. 【圖像分割論文閱讀】ENet：A Deep Neural Network Architecture for Real-Time Semantic Segmentation
- 6. 【圖像分割論文閱讀】The One Hundred Layers Tiramisu: Fully Convolutional DenseNets for Semantic Segmentation
- 7. 【圖像分割論文閱讀】ICNet for Real-Time Semantic Segmentation on High-Resolution Images
- 8. 圖像分割「LinkNet: Exploiting Encoder Representations for Efficient Semantic Segmentation」
- 9. 【圖像分割論文閱讀】OANet：An End-to-End Network for Panoptic Segmentation
- 10. LinkNet: Exploiting Encoder Representations for Efficient Semantic Segmentation論文閱讀