mlsanityData to 7 Oct 2026

CloudSegNet: A Deep Network for Nychthemeron Cloud Image Segmentation

arXiv 1904.07979 ↗First posted 16 Apr 2019physics.ao-ph cs.CV eess.IVcited by 15

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Abstract (arXiv)

We analyze clouds in the earth's atmosphere using ground-based sky cameras. An accurate segmentation of clouds in the captured sky/cloud image is difficult, owing to the fuzzy boundaries of clouds. Several techniques have been proposed that use color as the discriminatory feature for cloud detection. In the existing literature, however, analysis of daytime and nighttime images is considered separately, mainly because of differences in image characteristics and applications. In this paper, we propose a light-weight deep-learning architecture called CloudSegNet. It is the first that integrates daytime and nighttime (also known as nychthemeron) image segmentation in a single framework, and achieves state-of-the-art results on public databases.

Key facts. Cited by 15 papers in the map (data through 7 Oct 2026). First posted on arXiv 16 Apr 2019.

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Citing papers per year: 2021: 1; 2022: 5; 2023: 1; 2024: 1; 2025: 4; 2026: 3.

15 papers.

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  1. 2021Using GANs to Augment Data for Cloud Image Segmentation Taskcited by 6
  2. 2025DDUNet: Dual Dynamic U-Net for Highly-Efficient Cloud Segmentationcited by 6
  3. 2022Water Simulation and Rendering from a Still Photographcited by 5
  4. 2025UCloudNet: A Residual U-Net with Deep Supervision for Cloud Image Segmentationcited by 5
  5. 2022Using U-Net Network for Efficient Brain Tumor Segmentation in MRI Imagescited by 4
  6. 2022ACLNet: An Attention and Clustering-based Cloud Segmentation Networkcited by 2
  7. 2022Open-Source Ground-based Sky Image Datasets for Very Short-term Solar Forecasting, Cloud Analysis and Modeling: A Comprehensive Surveycited by 2
  8. 2026LenghuSky-8: An 8-Year All-Sky Cloud Dataset with Star-Aware Masks and Alt-Az Calibration for Segmentation and Nowcastingcited by 1
  9. 2022Frequency-centroid features for word recognition of non-native English speakerscited by 0
  10. 2023A knowledge-based data-driven (KBDD) framework for all-day identification of cloud types using satellite remote sensingcited by 0
  11. 2024Multi-scale gridded Gabor attention for cirrus segmentationcited by 0
  12. 2025Segregation and Context Aggregation Network for Real-time Cloud Segmentationcited by 0
3 more
  1. 2025MPCM-Net: Multi-scale network integrates partial attention convolution with Mamba for ground-based cloud image segmentationcited by 0
  2. 2026CloudMamba: An Uncertainty-Guided Dual-Scale Mamba Network for Cloud Detection in Remote Sensing Imagerycited by 0
  3. 2026Cross-Modal Hierarchical Fusion for from Multi-Sensor Ground Observationcited by 0