Abstract: We propose a convolutional autoencoder neural network for image classification in YCbCr color space to reduce computational complexity. We first learned local image features from image ...

Firstly, multi-scale wavelets are employed to initialize the convolutional kernels, endowing the model with strong feature extraction capabilities and enhancing its multi-resolution properties.

Model architecture diagram of the deep convolutional autoencoder ... To enhance the timeliness of warnings, it is recommended to use a deep autoencoder as a feature extraction model, utilizing the ...