Abstract: In this paper, we propose a new cascaded deep auto-encoder networks (CDAN) approach for face alignment. Our framework consists of a global exemplar-based deep auto-encoder network (GEDAN) ...

Abstract: This paper discusses the effectiveness of deep auto-encoder neural networks in visual reinforcement learning (RL) tasks. We propose a framework for combining the training of deep ...

Reference code for the paper: Deep White-Balance Editing (CVPR 2020). Our method is a deep learning multi-task framework for white-balance editing. The purpose of this repository is to make prototypes ...

Tensorflow implementation of a Deep Kernelized Auto Encoder (dkAE), aligned with the Time series Cluster Kernel (TCK), for learning vectorial representations of mutlivariate time series (MTS) with ...

Manifold learning, rooted in the manifold assumption, reveals low-dimensional structures within input data, positing that the data exists on a low-dimensional manifold within a high-dimensional ...

Since the effectiveness of extracting fault features is not high under traditional bearing fault diagnosis method, a bearing fault diagnosis method based on Deep Auto-encoder Network (DAEN) optimized ...

To address the difficulties in fusing multi-mode sensor data for complex industrial machinery, an adaptive deep coupling convolutional auto-encoder (ADCCAE) fusion method was proposed. First, the ...