mlsanityData to 14 Oct 2026

Combining UPerNet and ConvNeXt for Contrails Identification to reduce Global Warming

arXiv 2310.04808 ↗First posted 7 Oct 2023cs.CVcited by 0

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Abstract (arXiv)

Semantic segmentation is a critical tool in computer vision, applied in various domains like autonomous driving and medical imaging. This study focuses on aircraft contrail detection in global satellite images to improve contrail models and mitigate their impact on climate change.An innovative data preprocessing technique for NOAA GOES-16 satellite images is developed, using brightness temperature data from the infrared channel to create false-color images, enhancing model perception. To tackle class imbalance, the training dataset exclusively includes images with positive contrail labels.The model selection is based on the UPerNet architecture, implemented using the MMsegmentation library, with the integration of two ConvNeXt configurations for improved performance. Cross-entropy loss with positive class weights enhances contrail recognition. Fine-tuning employs the AdamW optimizer with a learning rate of 2.5 × 10-4.During inference, a multi-model prediction fusion strategy and a contrail determination threshold of 0.75 yield a binary prediction mask. RLE encoding is used for efficient prediction result organization.The approach achieves exceptional results, boasting a high Dice coefficient score, placing it in the top 5% of participating teams. This underscores the innovative nature of the segmentation model and its potential for enhanced contrail recognition in satellite imagery.For further exploration, the code and models are available on GitHub: urlhttps://github.com/biluko/2023GRIC.git.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 19 of its 48 references that are in the map. First posted on arXiv 7 Oct 2023.

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References · 19

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7 more
  1. 2018Unified Perceptual Parsing for Scene Understandingcited by 1,271
  2. 2020Image Segmentation Using Deep Learning: A Surveycited by 660
  3. 2014Semantic Image Segmentation with Deep Convolutional Nets and Fully Connected CRFscited by 554
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  6. 2020Optimization for Medical Image Segmentation: Theory and Practice when evaluating with Dice Score or Jaccard Indexcited by 52
  7. 2023OpenContrails: Benchmarking Contrail Detection on GOES-16 ABIcited by 4

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