mlsanityData to 14 Oct 2026

Road Extraction by Deep Residual U-Net

arXiv 1711.10684 ↗First posted 29 Nov 2017cs.CVcited by 333

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Abstract (arXiv)

Road extraction from aerial images has been a hot research topic in the field of remote sensing image analysis. In this letter, a semantic segmentation neural network which combines the strengths of residual learning and U-Net is proposed for road area extraction. The network is built with residual units and has similar architecture to that of U-Net. The benefits of this model is two-fold: first, residual units ease training of deep networks. Second, the rich skip connections within the network could facilitate information propagation, allowing us to design networks with fewer parameters however better performance. We test our network on a public road dataset and compare it with U-Net and other two state of the art deep learning based road extraction methods. The proposed approach outperforms all the comparing methods, which demonstrates its superiority over recently developed state of the arts.

Key facts. Cited by 333 papers in the map (data through 14 Oct 2026). First posted on arXiv 29 Nov 2017.

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2021: 49; 2022: 69; 2023: 79; 2024: 47; 2025: 61; 2026: 28.

333 papers.

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  1. 2021TransBTS: Multimodal Brain Tumor Segmentation Using Transformercited by 265
  2. 2021TransFuse: Fusing Transformers and CNNs for Medical Image Segmentationcited by 258
  3. 2022Medical Image Segmentation Review: The success of U-Netcited by 191
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  5. 2021DS-TransUNet:Dual Swin Transformer U-Net for Medical Image Segmentationcited by 126
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  7. 2021Shallow Attention Network for Polyp Segmentationcited by 107
  8. 2021A multi-centre polyp detection and segmentation dataset for generalisability assessmentcited by 63
  9. 2023Very high resolution canopy height maps from RGB imagery using self-supervised vision transformer and convolutional decoder trained on Aerial Lidarcited by 60
  10. 2021MSRF-Net: A Multi-Scale Residual Fusion Network for Biomedical Image Segmentationcited by 53
  11. 2022TransDeepLab: Convolution-Free Transformer-based DeepLab v3+ for Medical Image Segmentationcited by 43
  12. 2023CaraNet: Context Axial Reverse Attention Network for Segmentation of Small Medical Objectscited by 43
38 more
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  3. 2021A Comprehensive Study on Colorectal Polyp Segmentation with ResUNet++, Conditional Random Field and Test-Time Augmentationcited by 41
  4. 2023Lesion-aware Dynamic Kernel for Polyp Segmentationcited by 39
  5. 2022DCSAU-Net: A Deeper and More Compact Split-Attention U-Net for Medical Image Segmentationcited by 37
  6. 2022FCN-Transformer Feature Fusion for Polyp Segmentationcited by 37
  7. 2024MedCLIP-SAM: Bridging Text and Image Towards Universal Medical Image Segmentationcited by 37
  8. 2021FANet: A Feedback Attention Network for Improved Biomedical Image Segmentationcited by 36
  9. 2024Towards Vision-Language Geo-Foundation Model: A Surveycited by 36
  10. 2022Transforming medical imaging with Transformers? A comparative review of key properties, current progresses, and future perspectivescited by 33
  11. 2023Efficient automatic segmentation for multi-level pulmonary arteries: The PARSE challengecited by 28
  12. 2023Physics-Informed Computer Vision: A Review and Perspectivescited by 28
  13. 2022Assessing generalisability of deep learning-based polyp detection and segmentation methods through a computer vision challengecited by 27
  14. 2022Vox2Cortex: Fast Explicit Reconstruction of Cortical Surfaces from 3D MRI Scans with Geometric Deep Neural Networkscited by 27
  15. 2023A Unified Framework for U-Net Design and Analysiscited by 27
  16. 2022Landslide4Sense: Reference Benchmark Data and Deep Learning Models for Landslide Detectioncited by 26
  17. 2024Not All Diffusion Model Activations Have Been Evaluated as Discriminative Featurescited by 25
  18. 2022CKD-TransBTS: Clinical Knowledge-Driven Hybrid Transformer with Modality-Correlated Cross-Attention for Brain Tumor Segmentationcited by 24
  19. 2023Segmentation and Vascular Vectorization for Coronary Artery by Geometry-based Cascaded Neural Networkcited by 21
  20. 2022TransResU-Net: Transformer based ResU-Net for Real-Time Colonoscopy Polyp Segmentationcited by 19
  21. 2024Pick of the Bunch: Detecting Infrared Small Targets Beyond Hit-Miss Trade-Offs via Selective Rank-Aware Attentioncited by 17
  22. 2021NanoNet: Real-Time Polyp Segmentation in Video Capsule Endoscopy and Colonoscopycited by 16
  23. 2021Orthogonal Ensemble Networks for Biomedical Image Segmentationcited by 16
  24. 2024An objective comparison of methods for augmented reality in laparoscopic liver resection by preoperative-to-intraoperative image fusioncited by 16
  25. 2022CAT-Net: A Cross-Slice Attention Transformer Model for Prostate Zonal Segmentation in MRIcited by 15
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  27. 2024Neural deformation fields for template-based reconstruction of cortical surfaces from MRIcited by 14
  28. 2024Frontiers in Intelligent Colonoscopycited by 14
  29. 2021Maximum Entropy on Erroneous Predictions (MEEP): Improving model calibration for medical image segmentationcited by 13
  30. 2021HumanGPS: Geodesic PreServing Feature for Dense Human Correspondencescited by 12
  31. 2022DTU-Net: Learning Topological Similarity for Curvilinear Structure Segmentationcited by 12
  32. 2022Physiology-based simulation of the retinal vasculature enables annotation-free segmentation of OCT angiographscited by 12
  33. 2023An Accurate and Efficient Neural Network for OCTA Vessel Segmentation and a New Datasetcited by 12
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  35. 2025MK-UNet: Multi-kernel Lightweight CNN for Medical Image Segmentationcited by 12
  36. 2021CFPNet-M: A Light-Weight Encoder-Decoder Based Network for Multimodal Biomedical Image Real-Time Segmentationcited by 11
  37. 2022Learning-based Localizability Estimation for Robust LiDAR Localizationcited by 11
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