IEEE

XChange: An Explainable Dynamic Convolutional Autoencoder for Unsupervised Change Detection

Abstract: Explainable artificial intelligence (XAI) approaches started to be studied in the last period to improve the interpretability of increasingly complex deep learning (DL) methods for remote ...
Frontiers

A self-learning multimodal approach for fake news detection

The rapid growth of social media has resulted in an explosion of online news content, leading to a significant increase in the spread of misleading or false information. While machine learning ...
TMCnet

WiMi Lays Out Scalable Quantum Convolutional Neural Network to Enhance Image Classification Accuracy and Efficiency

BEIJING, Sept. 15, 2025 /PRNewswire/ -- WiMi Hologram Cloud Inc. (NASDAQ: WiMi) ("WiMi" or the "Company"), a leading global Hologram Augmented Reality ("AR") Technology provider, today announced that ...
IEEE

Conv4Rec: A 1-by-1 Convolutional Autoencoder for User Profiling Through Joint Analysis of Implicit and Explicit Feedback

Abstract: We introduce a new convolutional autoencoder architecture for user modeling and recommendation tasks with several improvements over the state of the art. First, our model has the flexibility ...
GitHub

autoencoder-mnist

Image Denoising with Autoencoders in R (University Project) Built a convolutional autoencoder in R using Keras/TensorFlow to perform image denoising on MNIST and CIFAR-10 datasets with varying levels ...
C&EN

DeepAIPs-SFLA: Deep Convolutional Model for Prediction of Anti-Inflammatory Peptides Using Binary Pattern Decomposition of Novel Multiview Descriptors with an SFLA Approach

Institute of Fundamental and Frontier Sciences, University of Electronic Science and Technology of China, Chengdu 610054, China ...
Frontiers

An abnormal traffic detection method for chain information management system network based on convolutional neural network

Chain information management system is widely used, providing convenience for the operation and management of enterprises. However, the problem of abnormal network traffic becomes increasingly ...
Scientific Research Publishing

Mao, X.J., Shen, C. and Yang, Y.B. (2016) Image Restoration Using Convolutional Auto-Encoders with Symmetric Skip Connections.

ABSTRACT: Convolutional auto-encoders have shown their remarkable performance in stacking deep convolutional neural networks for classifying image data during the past several years. However, they are ...