Automatic Pixelwise Object Labeling for Aerial Imagery Using Stacked U-Nets解读
摘要 - 航空影像中物体标记的自动化是一项计算机视觉任务，具有许多实际应用。像能源勘探这样的领域需要一种自动化方法来每天处理连续的图像流。在本文中，我们提出了一个流水线来解决这个问题，使用一堆端到端的卷积神经网络（U-Net架构）。每个网络都可以工作后处理器到前一个。我们的模型在两个不同的数据集上胜过当前的最新技术：Inria Aerial Image Labeling数据集和Massachus
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相关文章
- 1. Automatic Pixelwise Object Labeling for Aerial Imagery Using Stacked U-Nets 翻译
- 2. [论文解读] 3DOP: 3D Object Proposals using Stereo Imagery for Accurate Object Class Detection
- 3. Fully Convolutional Network for Automatic Road Extraction from Satellite Imagery
- 4. 【论文浅读】《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译文
- 7. 简读：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