To address these problems, this letter proposes a novel RGB-D image classification framework based on reduced biquaternion stacked denoising convolutional autoencoder (RQ-SDCAE). The proposed ...

and has not been applied to high-level image processing tasks such as image classification. The stacked convolutional autoencoder with fusion selection kernel attention mechanism is an unsupervised ...

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 ...

This project aims to develop an new approach to improve the performance of Convolutional Neural Networks (CNNs) for image classification by using Variational Autoencoder (VAE)-generated hybrid ...

In this paper, a novel deep neural network is proposed for emotion classification using EEG systems, which combines the Convolutional Neural Network (CNN), Sparse Autoencoder (SAE ... features are ...