wuchangsheng951 / GLNET

Convolutional Neural Networks Based Remote Sensing Scene Classification under Clear and Cloudy Environments

Convolutional Neural Networks Based Remote Sensing Scene Classification under Clear and Cloudy Environments

Accepted by ICCVW 2021

Remote Sensing scene image classification under clear and cloudy environments.

Overview architecture of the proposed GLNet for the RS scene classification under clear and cloudy environments.

Required libraries

python 3.6

pytorch 1.0+

numpy

PIl

torchvision

Usage

1. clone this repo

   git clone https://github.com/wuchangsheng951/GLNET.git
   

2. download the dataset from google drive

3. train the baseline model

   python baseline.py
   

4. load the model dir you trained in model.py

5. run the training by command

   python train.py
   

Citation

{Huiming Sun, Yuewei Lin, Qin Zou, Shaoyue Song, Jianwu Fang, Hongkai Yu. Convolutional Neural Networks Based Remote Sensing Scene Classification under Clear and Cloudy Environments. IEEE International Conference on Computer Vision Workshop (ICCVW), 2021.}