Paint Detection in Shortwave and Midwave Hyperspectral Using one Dimensional CNN and Guided Grad-CAM band selection

Short wave infrared (SWIR) is the reflected radiance in the 1-2.5 mu m range. Mid wave infrared (MWIR) is the radiated radiance in the 3-5 mu m range. This paper proposes a paint detection method using two infrared bands with different characteristics. Object detection is one of the issues in hyperspectral image (HSI). We use one dimensional convolution neural network (1D-CNN) and guided gradient-weighted class activation mapping (Guided Grad-CAM) for band selection. We make a 1D-CNN architecture and select bands using Guided Grad-CAM from well-trained 1D-CNN. Finally, paint is detected using selected bands. We use datasets included short wave infrared band (SWIR) and mid wave infrared band (MWIR).