Literatures on Deep Nets for Satellite Sensing - Githubissues

puria-radmard / satellite-cGAN

A Conditional Generative Adversarial Network (cGAN) approach to learning the effects of urban feature morphology on the urban heat island (UHI) effect

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Literatures on Deep Nets for Satellite Sensing #3

Open hansen7 opened 3 years ago

hansen7 commented 3 years ago

"Feature Pyramid Network for Multi-Class Land Segmentation", CVPRW 2018

hansen7 commented 3 years ago

"Combining satellite imagery and machine learning to predict poverty", Science 2016

hansen7 commented 3 years ago

"Using publicly available satellite imagery and deep learning to understand economic well-being in Africa", Nature Communication 2020

hansen7 commented 3 years ago

relevant materials from: https://github.com/robmarkcole/satellite-image-deep-learning

hansen7 commented 3 years ago

"Purely satellite data–driven deep learning forecast of complicated tropical instability waves", Science Advances 2020

hansen7 commented 3 years ago

https://www.sciencedirect.com/science/article/pii/S030324341831033X

hansen7 commented 3 years ago

relevant papers from these particular CVPR workshops:

hansen7 commented 3 years ago

"Geometry-Aware Satellite-to-Ground Image Synthesis for Urban Areas", CVPR 2020

hansen7 commented 3 years ago

Pixelwise regression task includes:

Monocular Depth Estimation
- Deep Ordinal Regression Network for Monocular Depth Estimation, CVPR 2018
Crowd Counting
- Learning from Synthetic Data for Crowd Counting in the Wild, CVPR 2019
- https://github.com/gjy3035/Awesome-Crowd-Counting/blob/master/src/Top_Conference-Journal.md