67 citations as recorded by crossref.

1. A Self Training Mechanism With Scanty and Incompletely Annotated Samples for Learning‐Based Cloud Detection in Whole Sky Images L. Ye et al.
2. A review on deep learning techniques for cloud detection methodologies and challenges L. Li et al.
3. Neural network processing of holographic images J. Schreck et al.
4. Machine Learning Models for Approximating Downward Short-Wave Radiation Flux over the Ocean from All-Sky Optical Imagery Based on DASIO Dataset M. Krinitskiy et al.
5. Neural Network-Based Solar Irradiance Forecast for Edge Computing Devices G. Venitourakis et al.
6. LSCIDMR: Large-Scale Satellite Cloud Image Database for Meteorological Research C. Bai et al.
7. Holistic and Lightweight Approach for Solar Irradiance Forecasting M. Jain et al.
8. Data-Driven Cloud Clustering via a Rotationally Invariant Autoencoder T. Kurihana et al.
9. Cloud detection using convolutional neural networks on remote sensing images L. Matsunobu et al.
10. Applying self-supervised learning for semantic cloud segmentation of all-sky images Y. Fabel et al.
11. Day and Night Clouds Detection Using a Thermal-Infrared All-Sky-View Camera Y. Wang et al.
12. Cloud-Cluster: An uncertainty clustering algorithm based on cloud model Y. Liu et al.
13. Feasibility of Ground-Based Sky-Camera HDR Imagery to Determine Solar Irradiance and Sky Radiance over Different Geometries and Sky Conditions P. Valdelomar et al.
14. CAFTrans: Content-Aware Fusion Transformer for ground-based remote sensing cloud detection S. Liu et al.
15. Cloud fraction estimation using random forest classifier on sky images S. Sarangi et al.
16. ACLNet: an attention and clustering-based cloud segmentation network D. Makwana et al.
17. Cloud Segmentation, Validation of Weather Data, and Precipitation Prediction Using Machine Learning Algorithms N. Rajendiran et al.
18. Advancing semantic cloud segmentation in all-sky images: A semi-supervised learning approach with ceilometer-driven weak labels D. Magiera et al.
19. Validation of a camera-based intra-hour irradiance nowcasting model using synthetic cloud data P. Gregor et al.
20. CloudFU-Net: A Fine-Grained Segmentation Method for Ground-Based Cloud Images Based on an Improved Encoder–Decoder Structure C. Shi et al.
21. ConvODE-Mixer: A multimodal deep learning model for ultra-short-term PV power forecasting B. Yong et al.
22. Segmentation and Celestial Mapping of Unobservable Regions in Nighttime All-sky Images for Mephisto Observations J. Cui et al.
23. Characterization of the vertical evolution of urban nocturnal boundary layer by UAV measurements: Insights into relations to cloud radiative effect L. Shen et al.
24. Creating Cloud Segmentation Data Set Using Sky Images of Afyonkarahisar Region A. Eşlik et al.
25. MPCM-Net: A Multiscale Network That Integrates Partial Attention Convolution With Mamba for Ground-Based Cloud Image Segmentation P. Niu et al.
26. CloudDeepLabV3+: a lightweight ground-based cloud segmentation method based on multi-scale feature aggregation and multi-level attention feature enhancement S. Li et al.
27. A dual attentional skip connection based Swin‐UNet for real‐time cloud segmentation F. Wei et al.
28. Cloud detection algorithm based on point by point refinement J. Zhang
29. A Novel Ground-Based Cloud Image Segmentation Method by Using Deep Transfer Learning Z. Zhou et al.
30. Ground-Based Remote Sensing Cloud Detection Using Dual Pyramid Network and Encoder–Decoder Constraint Z. Zhang et al.
31. CCAD-Net: A Cascade Cloud Attribute Discrimination Network for Cloud Genera Segmentation in Whole-Sky Images L. Ye et al.
32. BSANet: A Bilateral Segregation and Aggregation Network for Real-time Cloud Segmentation Y. Li et al.
33. Angular Calibration of Visible and Infrared Binocular All-Sky-View Cameras Using Sun Positions W. Xie et al.
34. Integration Transformer for Ground-Based Cloud Image Segmentation S. Liu et al.
35. Flow-Field Inference for Turbulent Exhale Flow Measurement S. Transue et al.
36. Twenty-four-hour cloud cover calculation using a ground-based imager with machine learning B. Kim et al.
37. Semantic segmentation of terrestrial whole-sky images using the new W-Net model with the stationary wavelet transform 2D D. Fantini et al.
38. Open-source sky image datasets for solar forecasting with deep learning: A comprehensive survey Y. Nie et al.
39. Nowcasting Solar Irradiance Components Using a Vision Transformer and Multimodal Data from All-Sky Images and Meteorological Observations O. Bayasgalan & A. Akisawa
40. Automatic localization and characterization of mid-latitude ionospheric plasma structures from all-sky airglow images using deep learning framework S. Chakrabarti et al.
41. Physics-Prior-Guided Feature Pyramid Network for Unified Multi-Angle Spectral–Polarimetric Cloud Detection S. Li et al.
42. Data augmentation and normalization strategies for improving satellite image segmentation A. Saadia et al.
43. Estimation of 24 h continuous cloud cover using a ground-based imager with a convolutional neural network B. Kim et al.
44. Ground-Based Cloud Detection Using Multiscale Attention Convolutional Neural Network Z. Zhang et al.
45. MSSEAG-UNet: A Novel Deep Learning Architecture for Cloud Segmentation in Fisheye Sky Images and Solar Energy Forecast A. Kumar et al.
46. Cloud detection method using ground-based sky images based on clear sky library and superpixel local threshold Y. Niu et al.
47. Cloud Segmentation and Matching Using Deep Learning in All-Sky Images N. Theis et al.
48. Experimental review and recent advances in deep learning techniques for solar irradiance forecasting and prediction C. Otuka et al.
49. TransCloudSeg: Ground-Based Cloud Image Segmentation With Transformer S. Liu et al.
50. A Novel Ground-Based Cloud Image Segmentation Method Based on a Multibranch Asymmetric Convolution Module and Attention Mechanism L. Zhang et al.
51. A Machine Learning Approach to Derive Aerosol Properties from All-Sky Camera Imagery F. Scarlatti et al.
52. Unmasking air quality: A novel image-based approach to align public perception with pollution levels T. Lin et al.
53. Cloud classification and cloud cover estimation using hybrid deep Kronecker network- ResNeXt G. Rudrappa & N. Vijapur
54. A fractional-order image segmentation model with application to low-contrast and piecewise smooth images J. Cao et al.
55. Infrared radiometric image classification and segmentation of cloud structures using a deep-learning framework from ground-based infrared thermal camera observations K. Sommer et al.
56. TransFCloudNet: a dual-branch feature fusion ground-based cloud image fine-grained segmentation method for photovoltaic power prediction Z. Su et al.
57. Advances in solar forecasting: Computer vision with deep learning Q. Paletta et al.
58. Cloud Detection and Tracking Based on Object Detection with Convolutional Neural Networks J. Carballo et al.
59. Region-specific design of trapezoidal membership functions for fuzzy hydrometeor classification: a statistical approach using ρHV-stratified ZH, , ZDR and KDP from C-band DWR data U. Sahoo et al.
60. MRR-YOLO: an instance segmentation technique for ground-based cloud images Z. Wan et al.
61. 双波段全天空云量观测系统研制及数据分析 王. Wang Yiren et al.
62. Ground-Based Remote Sensing Cloud Image Segmentation Using Convolution-MLP Network S. Liu et al.
63. Burned area semantic segmentation: A novel dataset and evaluation using convolutional networks T. Ribeiro et al.
64. Ultra-short-term photovoltaic power prediction based on ground-based cloud images: A review C. Shi et al.
65. CloudSwinNet: A hybrid CNN-transformer framework for ground-based cloud images fine-grained segmentation C. Shi et al.
66. Hybrid Cloud Detection Algorithm Based on Intelligent Scene Recognition F. Li et al.
67. ResAG-UNet: A Novel Residual Attention Gated UNet for Cloud Segmentation in Sky Image A. Kumar et al.