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利用残差网络进行图像融合

  • Category : AI-NN-PR
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  • Update : 2018-11-29
  • Size : 13.06mb
  • Downloaded :0次
  • Author :mastein_feng
  • About : Nobody
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Introduction - If you have any usage issues, please Google them yourself
利用深度学习的方法进行红外图像和可见光图像的融合,该方法受启发于最近比较流行的迁移学习,利用可见光的数据集训练网络,从而提取出红外和可见光图像的特征,最后进行图像的融合。
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Packet : imagefusion_resnet50-master(1).zip filelist
imagefusion_resnet50-master/
imagefusion_resnet50-master/IV_images/
imagefusion_resnet50-master/IV_images/IV_images.zip
imagefusion_resnet50-master/README.md
imagefusion_resnet50-master/experiment_data/
imagefusion_resnet50-master/experiment_data/resnet_zca_IV.xlsx
imagefusion_resnet50-master/figures/
imagefusion_resnet50-master/figures/framework.png
imagefusion_resnet50-master/figures/results.png
imagefusion_resnet50-master/figures/soft_max.png
imagefusion_resnet50-master/figures/zca_l1norm.png
imagefusion_resnet50-master/figures/zca_operation.png
imagefusion_resnet50-master/fused_infrared/
imagefusion_resnet50-master/fused_infrared/fused_infrared.zip
imagefusion_resnet50-master/fusion_method_ResNet50_main.m
imagefusion_resnet50-master/fusion_strategy.m
imagefusion_resnet50-master/make_3c.m
imagefusion_resnet50-master/models/
imagefusion_resnet50-master/models/README.md
imagefusion_resnet50-master/whitening_norm.m
imagefusion_resnet50-master/zca.m
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