SEMANTIC SEGMENTATION OF AERIAL IMAGES WITH AN ENSEMBLE OF CNNS

91 citations as recorded by crossref.

1. An ensemble architecture of deep convolutional Segnet and Unet networks for building semantic segmentation from high-resolution aerial images A. Abdollahi et al. 10.1080/10106049.2020.1856199
2. On Circuit-Based Hybrid Quantum Neural Networks for Remote Sensing Imagery Classification A. Sebastianelli et al. 10.1109/JSTARS.2021.3134785
3. Extraction and spatiotemporal analysis of impervious surfaces in Chongqing based on enhanced DeepLabv3+ D. Wei et al. 10.1038/s41598-025-94882-6
4. Deep Learning Based Greenhouse Image Segmentation and Shoot Phenotyping (DeepShoot) N. Narisetti et al. 10.3389/fpls.2022.906410
5. Uncertainty-Based Human-in-the-Loop Deep Learning for Land Cover Segmentation C. García Rodríguez et al. 10.3390/rs12223836
6. Generalized Sparse Convolutional Neural Networks for Semantic Segmentation of Point Clouds Derived from Tri-Stereo Satellite Imagery S. Bachhofner et al. 10.3390/rs12081289
7. Aerial and Optical Images-Based Plant Species Segmentation Using Enhancing Nested Downsampling Features C. Lin et al. 10.3390/f12121695
8. HENet: Head-Level Ensemble Network for Very High Resolution Remote Sensing Images Semantic Segmentation Y. Cao et al. 10.1109/LGRS.2022.3147857
9. Deep-Learning-Based Land Cover Mapping in Franciacorta Wine Growing Area G. Tariku et al. 10.3390/app15020871
10. CscGAN: Conditional Scale-Consistent Generation Network for Multi-Level Remote Sensing Image to Map Translation Y. Liu et al. 10.3390/rs13101936
11. Planetary Mapping Using Deep Learning: A Method to Evaluate Feature Identification Confidence Applied to Habitats in Mars-Analog Terrain M. Phillips et al. 10.1089/ast.2022.0014
12. Deep learning algorithms to isolate and quantify the structures of the anterior segment in optical coherence tomography images T. Pham et al. 10.1136/bjophthalmol-2019-315723
13. Multiclass Land Cover Mapping from Historical Orthophotos Using Domain Adaptation and Spatio-Temporal Transfer Learning W. Van den Broeck et al. 10.3390/rs14235911
14. Identifying Informal Settlements Using Contourlet Assisted Deep Learning R. Ansari et al. 10.3390/s20092733
15. U-Net Ensemble for Enhanced Semantic Segmentation in Remote Sensing Imagery I. Dimitrovski et al. 10.3390/rs16122077
16. Portrait Segmentation Using Ensemble of Heterogeneous Deep-Learning Models Y. Kim et al. 10.3390/e23020197
17. PGNet: Positioning Guidance Network for Semantic Segmentation of Very-High-Resolution Remote Sensing Images B. Liu et al. 10.3390/rs14174219
18. Convolutional Neural Network for Thailand's Eastern Economic Corridor (EEC) land cover classification using overlapping process on satellite images P. Chermprayong et al. 10.1016/j.rsase.2021.100543
19. DensePPMUNet-a: A Robust Deep Learning Network for Segmenting Water Bodies From Aerial Images D. Xiang et al. 10.1109/TGRS.2023.3251659
20. Application of deep learning for semantic segmentation of sandstone thin sections N. Saxena et al. 10.1016/j.cageo.2021.104778
21. C3Net: Cross-Modal Feature Recalibrated, Cross-Scale Semantic Aggregated and Compact Network for Semantic Segmentation of Multi-Modal High-Resolution Aerial Images Z. Cao et al. 10.3390/rs13030528
22. An End-to-End Atrous Spatial Pyramid Pooling and Skip-Connections Generative Adversarial Segmentation Network for Building Extraction from High-Resolution Aerial Images M. Yu et al. 10.3390/app12105151
23. Urban Land-Cover Classification Using Side-View Information from Oblique Images C. Xiao et al. 10.3390/rs12030390
24. Building Extraction in Very High Resolution Remote Sensing Imagery Using Deep Learning and Guided Filters Y. Xu et al. 10.3390/rs10010144
25. Building Extraction of Aerial Images by a Global and Multi-Scale Encoder-Decoder Network J. Ma et al. 10.3390/rs12152350
26. Fully‐connected semantic segmentation of hyperspectral and LiDAR data H. Aytaylan & S. Yuksel 10.1049/iet-cvi.2018.5067
27. A review of deep learning methods for semantic segmentation of remote sensing imagery X. Yuan et al. 10.1016/j.eswa.2020.114417
28. A deep learning approach to identify smoke plumes in satellite imagery in near-real time for health risk communication A. Larsen et al. 10.1038/s41370-020-0246-y
29. Deep learning based high performance classification architecture for low-altitude aerial images P. Mittal et al. 10.1007/s11042-023-16195-y
30. Convolutional Neural Network for Convolution of Aerial Survey Images N. Trong et al. 10.1016/j.ifacol.2021.10.513
31. High resolution remote sensing recognition of elm sparse forest via deep-learning-based semantic segmentation H. Liu et al. 10.1016/j.ecolind.2024.112428
32. Domain Adaptation for Semantic Segmentation of Historical Panchromatic Orthomosaics in Central Africa N. Mboga et al. 10.3390/ijgi10080523
33. Geoscience-aware deep learning: A new paradigm for remote sensing Y. Ge et al. 10.1016/j.srs.2022.100047
34. Application of Deep Learning for Delineation of Visible Cadastral Boundaries from Remote Sensing Imagery S. Crommelinck et al. 10.3390/rs11212505
35. From multi-sensor aerial data to thermal and infrared simulation of semantic 3D models: Towards identification of urban heat islands D. Bulatov et al. 10.1016/j.infrared.2020.103233
36. Dense Semantic Labeling with Atrous Spatial Pyramid Pooling and Decoder for High-Resolution Remote Sensing Imagery Y. Wang et al. 10.3390/rs11010020
37. Hierarchical spatial features learning with deep CNNs for very high-resolution remote sensing image classification G. Zhang et al. 10.1080/01431161.2018.1506593
38. Exploiting semantic segmentation to boost reinforcement learning in video game environments J. Montalvo et al. 10.1007/s11042-022-13695-1
39. Semantic Segmentation of Some Rock-Forming Mineral Thin Sections Using Deep Learning Algorithms: A Case Study from the Nikeiba Area, South Eastern Desert, Egypt S. Hassan et al. 10.3390/rs16132276
40. Combining Deep Semantic Segmentation Network and Graph Convolutional Neural Network for Semantic Segmentation of Remote Sensing Imagery S. Ouyang & Y. Li 10.3390/rs13010119
41. A Deep Learning-Based Framework for Automated Extraction of Building Footprint Polygons from Very High-Resolution Aerial Imagery Z. Li et al. 10.3390/rs13183630
42. Orchard monitoring based on unmanned aerial vehicles and image processing by artificial neural networks: a systematic review D. Popescu et al. 10.3389/fpls.2023.1237695
43. Bayesian U-Net: Estimating Uncertainty in Semantic Segmentation of Earth Observation Images C. Dechesne et al. 10.3390/rs13193836
44. Instance-Level Scaling and Dynamic Margin-Alignment Knowledge Distillation for Remote Sensing Image Scene Classification C. Li et al. 10.3390/rs16203853
45. Automatic and Semantically-Aware 3D UAV Flight Planning for Image-Based 3D Reconstruction T. Koch et al. 10.3390/rs11131550
46. FURSformer: Semantic Segmentation Network for Remote Sensing Images with Fused Heterogeneous Features Z. Zhang et al. 10.3390/electronics12143113
47. A Review of Landcover Classification with Very-High Resolution Remotely Sensed Optical Images—Analysis Unit, Model Scalability and Transferability R. Qin & T. Liu 10.3390/rs14030646
48. No cell is an island: characterising the leaf epidermis usingepidermalmorph,a new R package M. Brown & G. Jordan 10.1111/nph.18519
49. Fine-Grained Abandoned Cropland Mapping in Southern China Using Pixel Attention Contrastive Learning H. Li et al. 10.1109/JSTARS.2023.3338454
50. Common Practices and Taxonomy in Deep Multiview Fusion for Remote Sensing Applications F. Mena et al. 10.1109/JSTARS.2024.3361556
51. Assessing Deep Convolutional Neural Networks and Assisted Machine Perception for Urban Mapping Y. Shao et al. 10.3390/rs13081523
52. CCANet: Class-Constraint Coarse-to-Fine Attentional Deep Network for Subdecimeter Aerial Image Semantic Segmentation G. Deng et al. 10.1109/TGRS.2021.3055950
53. Effective Fusion of Multi-Modal Remote Sensing Data in a Fully Convolutional Network for Semantic Labeling W. Zhang et al. 10.3390/rs10010052
54. Multi‐task fully convolutional networks for building segmentation on SAR image Z. Zhang et al. 10.1049/joe.2019.0569
55. Fully automatic image segmentation based on FCN and graph cuts Z. Wang et al. 10.1007/s00530-022-00945-3
56. Classification of satellite images for ecology management using deep features obtained from convolutional neural network models E. Özbay & M. Yıldırım 10.1007/s42044-022-00133-6
57. Training Small Networks for Scene Classification of Remote Sensing Images via Knowledge Distillation G. Chen et al. 10.3390/rs10050719
58. Pixel-Wise Classification Method for High Resolution Remote Sensing Imagery Using Deep Neural Networks R. Guo et al. 10.3390/ijgi7030110
59. Fusion of hierarchical class graphs for remote sensing semantic segmentation X. Kang et al. 10.1016/j.inffus.2024.102409
60. A Novel Object-Based Deep Learning Framework for Semantic Segmentation of Very High-Resolution Remote Sensing Data: Comparison with Convolutional and Fully Convolutional Networks M. Papadomanolaki et al. 10.3390/rs11060684
61. A Modification method based on U-Net for the distorted pseudo edge of aerial initial orthophoto J. Xiong et al. 10.1088/1742-6596/1922/1/012006
62. Integration of Convolutional Neural Networks and Object-Based Post-Classification Refinement for Land Use and Land Cover Mapping with Optical and SAR Data S. Liu et al. 10.3390/rs11060690
63. FMnet: Iris Segmentation and Recognition by Using Fully and Multi-Scale CNN for Biometric Security R. Tobji et al. 10.3390/app9102042
64. Building Multi-Feature Fusion Refined Network for Building Extraction from High-Resolution Remote Sensing Images S. Ran et al. 10.3390/rs13142794
65. Comparing the Semantic Segmentation of High-Resolution Images Using Deep Convolutional Networks: SegNet, HRNet, CSE-HRNet and RCA-FCN N. Sadeghi et al. 10.61186/jist.39680.11.44.359
66. FactSeg: Foreground Activation-Driven Small Object Semantic Segmentation in Large-Scale Remote Sensing Imagery A. Ma et al. 10.1109/TGRS.2021.3097148
67. Flood susceptibility mapping using convolutional neural network frameworks Y. Wang et al. 10.1016/j.jhydrol.2019.124482
68. Semantic Segmentation of Satellite Images using 2 various U-Net Architectures: A Comparison Study N. Gonthina & . L.V. Narasimha Prasad 10.22399/ijcesen.1360
69. Building Corner Detection in Aerial Images with Fully Convolutional Networks W. Song et al. 10.3390/s19081915
70. Automatic Building Footprint Extraction from Multi-Resolution Remote Sensing Images Using a Hybrid FCN P. Schuegraf & K. Bittner 10.3390/ijgi8040191
71. Fully-automated root image analysis (faRIA) N. Narisetti et al. 10.1038/s41598-021-95480-y
72. Retinal Disease Detection Using Deep Learning Techniques: A Comprehensive Review S. Muchuchuti & S. Viriri 10.3390/jimaging9040084
73. Semantic Segmentation of Remote-Sensing Images Through Fully Convolutional Neural Networks and Hierarchical Probabilistic Graphical Models M. Pastorino et al. 10.1109/TGRS.2022.3141996
74. Nonlocal CNN SAR Image Despeckling D. Cozzolino et al. 10.3390/rs12061006
75. Multi-Modality and Multi-Scale Attention Fusion Network for Land Cover Classification from VHR Remote Sensing Images T. Lei et al. 10.3390/rs13183771
76. Scale-aware spatial pyramid pooling with both encoder-mask and scale-attention for semantic segmentation F. Zhou et al. 10.1016/j.neucom.2019.11.042
77. JSH-Net: joint semantic segmentation and height estimation using deep convolutional networks from single high-resolution remote sensing imagery B. Zhang et al. 10.1080/01431161.2022.2135410
78. High-Movement Human Segmentation in Video Using Adaptive N-Frames Ensemble Y. Kim et al. 10.32604/cmc.2022.028632
79. LoveNAS: Towards multi-scene land-cover mapping via hierarchical searching adaptive network J. Wang et al. 10.1016/j.isprsjprs.2024.01.011
80. Deep Convolutional Neural Network for Flood Extent Mapping Using Unmanned Aerial Vehicles Data A. Gebrehiwot et al. 10.3390/s19071486
81. Performance evaluation of three deep learning models in building footprint extraction from aerial and satellite images N. Ahmadian et al. 10.61186/jgit.11.1.105
82. Real-Time Dense Semantic Labeling with Dual-Path Framework for High-Resolution Remote Sensing Image Y. Wang et al. 10.3390/rs11243020
83. Toward the automatic detection of effective gerbil holes in desert grasslands through unmanned aerial vehicle imagery G. Qi et al. 10.1080/10106049.2023.2215722
84. Deep Learning-Based Semantic Segmentation of Urban Features in Satellite Images: A Review and Meta-Analysis B. Neupane et al. 10.3390/rs13040808
85. UAVs in Disaster Management: Application of Integrated Aerial Imagery and Convolutional Neural Network for Flood Detection H. Munawar et al. 10.3390/su13147547
86. Learning Dual Multi-Scale Manifold Ranking for Semantic Segmentation of High-Resolution Images M. Zhang et al. 10.3390/rs9050500
87. DeepNoise: Signal and Noise Disentanglement Based on Classifying Fluorescent Microscopy Images via Deep Learning S. Yang et al. 10.1016/j.gpb.2022.12.007
88. Transformer and CNN Hybrid Deep Neural Network for Semantic Segmentation of Very-High-Resolution Remote Sensing Imagery C. Zhang et al. 10.1109/TGRS.2022.3144894
89. Segment-before-Detect: Vehicle Detection and Classification through Semantic Segmentation of Aerial Images N. Audebert et al. 10.3390/rs9040368
90. A real-time efficient object segmentation system based on U-Net using aerial drone images I. Ahmed et al. 10.1007/s11554-021-01166-z
91. High-Resolution U-Net: Preserving Image Details for Cultivated Land Extraction W. Xu et al. 10.3390/s20154064