Automatic Pixelwise Object Labeling for Aerial Imagery Using Stacked U-Nets解讀
摘要 - 航空影像中物體標記的自動化是一項計算機視覺任務，具有許多實際應用。像能源勘探這樣的領域需要一種自動化方法來每天處理連續的圖像流。在本文中，我們提出了一個流水線來解決這個問題，使用一堆端到端的卷積神經網絡（U-Net架構）。每個網絡都可以工作後處理器到前一個。我們的模型在兩個不同的數據集上勝過當前的最新技術：Inria Aerial Image Labeling數據集和Massachus
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相關文章
- 1. Automatic Pixelwise Object Labeling for Aerial Imagery Using Stacked U-Nets 翻譯
- 2. [論文解讀] 3DOP: 3D Object Proposals using Stereo Imagery for Accurate Object Class Detection
- 3. Fully Convolutional Network for Automatic Road Extraction from Satellite Imagery
- 4. 【論文淺讀】《Contextual Pyramid Attention Network for Building Segmentation in Aerial Imagery》
- 5. Note_ Can Semantic Labeling Methods Generalize to Any City The Inria Aerial Image Labeling Benchmark
- 6. Deep Multimodal Vehicle Detection in Aerial ISR Imagery譯文
- 7. 簡讀：Object-Aware Instance Labeling for Weakly Supervised Object Detection
- 8. Learning Hierarchical Features for Scene Labeling
- 9. Enhancing Underwater Imagery using Generative Adversarial Networks
- 10. Using Object Information for Spotting Text