SEMANTIC SEGMENTATION OF AERIAL IMAGES WITH AN ENSEMBLE OF CNNS

44 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. Multi‐task fully convolutional networks for building segmentation on SAR image Z. Zhang et al. 10.1049/joe.2019.0569
3. Deep Learning Based Greenhouse Image Segmentation and Shoot Phenotyping (DeepShoot) N. Narisetti et al. 10.3389/fpls.2022.906410
4. Fully automatic image segmentation based on FCN and graph cuts Z. Wang et al. 10.1007/s00530-022-00945-3
5. 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
6. Aerial and Optical Images-Based Plant Species Segmentation Using Enhancing Nested Downsampling Features C. Lin et al. 10.3390/f12121695
7. CscGAN: Conditional Scale-Consistent Generation Network for Multi-Level Remote Sensing Image to Map Translation Y. Liu et al. 10.3390/rs13101936
8. 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
9. 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
10. 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
11. PGNet: Positioning Guidance Network for Semantic Segmentation of Very-High-Resolution Remote Sensing Images B. Liu et al. 10.3390/rs14174219
12. Flood susceptibility mapping using convolutional neural network frameworks Y. Wang et al. 10.1016/j.jhydrol.2019.124482
13. 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
14. Fully-automated root image analysis (faRIA) N. Narisetti et al. 10.1038/s41598-021-95480-y
15. Application of deep learning for semantic segmentation of sandstone thin sections N. Saxena et al. 10.1016/j.cageo.2021.104778
16. 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
17. Retinal Disease Detection Using Deep Learning Techniques: A Comprehensive Review S. Muchuchuti & S. Viriri 10.3390/jimaging9040084
18. A review of deep learning methods for semantic segmentation of remote sensing imagery X. Yuan et al. 10.1016/j.eswa.2020.114417
19. 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
20. Deep learning based high performance classification architecture for low-altitude aerial images P. Mittal et al. 10.1007/s11042-023-16195-y
21. Multi-Modality and Multi-Scale Attention Fusion Network for Land Cover Classification from VHR Remote Sensing Images T. Lei et al. 10.3390/rs13183771
22. Convolutional Neural Network for Convolution of Aerial Survey Images N. Trong et al. 10.1016/j.ifacol.2021.10.513
23. 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
24. Domain Adaptation for Semantic Segmentation of Historical Panchromatic Orthomosaics in Central Africa N. Mboga et al. 10.3390/ijgi10080523
25. Geoscience-aware deep learning: A new paradigm for remote sensing Y. Ge et al. 10.1016/j.srs.2022.100047
26. A Prior Level Fusion Approach for the Semantic Segmentation of 3D Point Clouds Using Deep Learning Z. Ballouch et al. 10.3390/rs14143415
27. 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
28. 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
29. Hierarchical spatial features learning with deep CNNs for very high-resolution remote sensing image classification G. Zhang et al. 10.1080/01431161.2018.1506593
30. Exploiting semantic segmentation to boost reinforcement learning in video game environments J. Montalvo et al. 10.1007/s11042-022-13695-1
31. High-Movement Human Segmentation in Video Using Adaptive N-Frames Ensemble Y. Kim et al. 10.32604/cmc.2022.028632
32. 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
33. 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
34. 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
35. 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
36. Bayesian U-Net: Estimating Uncertainty in Semantic Segmentation of Earth Observation Images C. Dechesne et al. 10.3390/rs13193836
37. Deep Learning-Based Semantic Segmentation of Urban Features in Satellite Images: A Review and Meta-Analysis B. Neupane et al. 10.3390/rs13040808
38. FURSformer: Semantic Segmentation Network for Remote Sensing Images with Fused Heterogeneous Features Z. Zhang et al. 10.3390/electronics12143113
39. UAVs in Disaster Management: Application of Integrated Aerial Imagery and Convolutional Neural Network for Flood Detection H. Munawar et al. 10.3390/su13147547
40. 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
41. No cell is an island: characterising the leaf epidermis using epidermalmorph, a new R package M. Brown & G. Jordan 10.1111/nph.18519
42. 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
43. Assessing Deep Convolutional Neural Networks and Assisted Machine Perception for Urban Mapping Y. Shao et al. 10.3390/rs13081523
44. 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