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README.md

@@ -1796,7 +1796,7 @@ Clouds are a major issue in remote sensing images as they can obscure the underl
 
   7.40. [CloudMattingGAN](https://github.com/flyakon/CloudMattingGAN) -> code for 2019 paper: Generative Adversarial Training for Weakly Supervised Cloud Matting
 
-  7.41. [atrain-cloudseg](https://github.com/seanremy/atrain-cloudseg) -> Official repository for the A-Train Cloud Segmentation Dataset
+  7.41. [km_predict](https://github.com/kappazeta/km_predict) -> KappaMask, or km-predict, is a cloud detector for Sentinel-2 Level-1C and Level-2A input products applied to S2 full image prediction
 
   7.42. [CDnet](https://github.com/nkszjx/CDnet-pytorch-master) -> code for 2019 paper: CNN-Based Cloud Detection for Remote Sensing Imager
 
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   7.61. [DeCloud-GAN](https://github.com/pixiedust18/DeCloud-GAN) -> code for 2021 paper: DeCloud GAN: An Advanced Generative Adversarial Network for Removing Cloud Cover in Optical Remote Sensing Imagery
 
-  7.62. [km_predict](https://github.com/kappazeta/km_predict) -> KappaMask, or km-predict, is a cloud detector for Sentinel-2 Level-1C and Level-2A input products applied to S2 full image prediction
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 ## 8. Change detection
 
@@ -3394,19 +3392,16 @@ Measure surface contours & locate 3D points in space from 2D images. NeRF stands
 
   32.38. [Mapping drainage ditches in forested landscapes using deep learning and aerial laser scanning](https://github.com/williamlidberg/Mapping-drainage-ditches-in-forested-landscapes-using-deep-learning-and-aerial-laser-scanning)
 
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 ## 33. Thermal Infrared
 
 Thermal infrared remote sensing is a technique used to detect and measure thermal radiation emitted from the Earth’s surface. This technique can be used to measure the temperature of the ground and any objects on it and can detect the presence of different materials. Thermal infrared remote sensing is used to assess land cover, detect land-use changes, and monitor urban heat islands, as well as to measure the temperature of the ground during nighttime or in areas of limited visibility.
 
   33.1. [The World Needs (a lot) More Thermal Infrared Data from Space](https://towardsdatascience.com/the-world-needs-a-lot-more-thermal-infrared-data-from-space-dbbba389be8a)
 
-  33.2. [IR2VI thermal-to-visible image translation framework based on GANs](https://arxiv.org/abs/1806.09565) with [code](https://github.com/linty5/IR2VI_CycleGAN)
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-  33.3. [Object_Classification_in_Thermal_Images](https://www.researchgate.net/publication/328400392_Object_Classification_in_Thermal_Images_using_Convolutional_Neural_Networks_for_Search_and_Rescue_Missions_with_Unmanned_Aerial_Systems) -> classification accuracy was improved by adding the object size as a feature directly within the CNN
+  33.2. [Object_Classification_in_Thermal_Images](https://www.researchgate.net/publication/328400392_Object_Classification_in_Thermal_Images_using_Convolutional_Neural_Networks_for_Search_and_Rescue_Missions_with_Unmanned_Aerial_Systems) -> classification accuracy was improved by adding the object size as a feature directly within the CNN
 
-  33.4. [Thermal imaging with satellites](https://chrieke.medium.com/thermal-imaging-with-satellites-34f381856dd1) blog post by Christoph Rieke
+  33.3. [Thermal imaging with satellites](https://chrieke.medium.com/thermal-imaging-with-satellites-34f381856dd1) blog post by Christoph Rieke
 
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 ## 34. SAR