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Self-Attention-Based Deep Feature Fusion for Remote Sensing Scene Classification

Use vgg16 and SAFF for small sample classification from the paper.

Introduction

  • Extract dataset features using pretrained vgg16

  • SAFF converts features into 1D tensor

Environmental preparation

conda create -n zh python=3.9
conda activate zh
python3 -m pip install --upgrade pip
pip3 install -r requirements.txt

Run

If your dataset is at path /hy-tmp/data Suppose you want to train on the UC dataset.

  • Feature extraction
python run.py 
--data_path /hy-tmp/data 
--extract
--dataset UC
  • Train & verify
python run.py 
--data_path /hy-tmp/data
--train
--dataset UC
--ratio 0.8

Experimental results

dataset train_ratio acc
NWPU 0.1 66.49
NWPU 0.2 73.13
UC 0.8 92.5
SAR 0.8 89.8

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