Road Extraction by Deep Residual U-Net
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- Type
- article
- Published
- 2017-11-29
- Cited by
- 2,782
- References
- 27
- Access
- Open access
- OpenAlex
- https://openalex.org/W2774320778
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:206437632
Keywords
Residual, Computer science, Deep learning, Segmentation, Artificial intelligence
References
- Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks
- Relaxed Precision and Recall for Ontology Matching
- Very Deep Convolutional Networks for Large-Scale Image Recognition
- Fully convolutional networks for semantic segmentation
- Road Network Detection Using Probabilistic and Graph Theoretical Methods
- Road centreline extraction from high‐resolution imagery based on multiscale structural features and support vector machines
- Urban road extraction via graph cuts based probability propagation
- Going deeper with convolutions
- Road Extraction Using SVM and Image Segmentation
- Learning Deep Features for Scene Recognition using Places Database
- Use of Salient Features for the Design of a Multistage Framework to Extract Roads From High-Resolution Multispectral Satellite Images
- Connected component-based technique for automatic extraction of road centerline in high resolution satellite images
- Deep Residual Learning for Image Recognition
- Main Road Extraction from ZY-3 Grayscale Imagery Based on Directional Mathematical Morphology and VGI Prior Knowledge in Urban Areas
- Learning to Label Aerial Images from Noisy Data
- Road Centerline Extraction via Semisupervised Segmentation and Multidirection Nonmaximum Suppression
- Deep Learning for Remote Sensing Data: A Technical Tutorial on the State of the Art
- Multiple Object Extraction from Aerial Imagery with Convolutional Neural Networks
- A CNN based functional zone classification method for aerial images
- CNN based suburban building detection using monocular high resolution Google Earth images
Cited by
- Road Segmentation in SAR Satellite Images With Deep Fully Convolutional Neural Networks
- Recurrent Residual Convolutional Neural Network based on U-Net (R2U-Net) for Medical Image Segmentation
- A survey on deep learning techniques for image and video semantic segmentation
- Rethinking Radiology: An Analysis of Different Approaches to BraTS
- Pixel-wise regression using U-Net and its application on pansharpening
- Fully Convolutional Network for Automatic Road Extraction from Satellite Imagery
- Deep neural network for pixel-level electromagnetic particle identification in the MicroBooNE liquid argon time projection chamber
- Road Extraction From a High Spatial Resolution Remote Sensing Image Based on Richer Convolutional Features
- Road Extraction from High-Resolution Remote Sensing Imagery Using Deep Learning
- ScatterNet: A convolutional neural network for cone‐beam CT intensity correction
- Deep Dual Loss BRDF Parameter Estimation
- D-LinkNet: LinkNet with Pretrained Encoder and Dilated Convolution for High Resolution Satellite Imagery Road Extraction
- Satellite Imagery Multiscale Rapid Detection with Windowed Networks
- DeepCMB: Lensing Reconstruction of the Cosmic Microwave Background with Deep Neural Networks
- Extreme Augmentation : Can deep learning based medical image segmentation be trained using a single manually delineated scan?
- Deep Learning Seismic Interface Detection using the Frozen Gaussian Approximation
- CPNet: A Context Preserver Convolutional Neural Network for Detecting Shadows in Single RGB Images
- Towards Operational Satellite-Based Damage-Mapping Using U-Net Convolutional Network: A Case Study of 2011 Tohoku Earthquake-Tsunami
- Urban Land Use and Land Cover Classification Using Novel Deep Learning Models Based on High Spatial Resolution Satellite Imagery
- Road Segmentation Based on Hybrid Convolutional Network for High-Resolution Visible Remote Sensing Image
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