Changan Automobile Applies for Driving Style Recognition Patent: Can Expert Models Revolutionize Future Driving Experience?

Changan Automobile Applies for Driving Style Recognition Patent, Leading a New Trend in Intelligent Driving ...

Changan Automobile Applies for Driving Style Recognition Patent: Can AI See Through Your Driving Habits?

Data shows that over 60% of drivers exhibit irregular behaviors while driving, such as sudden acceleration and frequent lane changes. These behaviors not only affect driving safety but may also ...
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 ...
IEEE

An Elliptic Kernel Unsupervised Autoencoder—Graph Convolutional Network Ensemble Model for Hyperspectral Unmixing

Abstract: Spectral unmixing is an important technique in remote sensing for analyzing hyperspectral images to identify endmembers and estimate fractional abundance maps. Over the past few decades, ...
Frontiers

Enhancing security in 6G-enabled wireless sensor networks for smart cities: a multi-deep learning intrusion detection approach

Introduction: Wireless Sensor Networks (WSNs) play a critical role in the development of sustainable and intelligent smart city infrastructures, enabling data-driven services such as smart mobility, ...
Scientific Research Publishing

Sun, Y., Xue, B., Zhang, M. and Yen, G.G. (2019) A Particle Swarm Optimization-Based Flexible Convolutional Autoencoder for Image Classification. IEEE Transactions on Neural ...

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 ...
Scientific Research Publishing

Li, Z., Yang, W., Peng, S., et al. (2020) A Survey of Convolutional Neural Networks: Analysis, Applications, and Prospects.

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 ...
GitHub

Deepfake Video Detection Using Generative Convolutional Vision Transformer

This repository contains the implementation code for Deepfake Video Detection Using Generative Convolutional Vision Transformer (GenConViT) paper. Find the full paper on arXiv here. The Proposed ...
GitHub

A quantised temporal convolutional autoencoder deployed on the PYNQ-Z2 FPGA using the FINN framework.

The model architecture, training, and validation can be found in the QuantisedAutoEncoder.ipynb Python Jupyter Notebook This part of the project was done using the Google Drive and Google Colab, and ...
Frontiers

Enhanced heart sound anomaly detection via WCOS: a semi-supervised framework integrating wavelet, autoencoder and SVM

Anomaly detection is a typical binary classification problem under the condition of unbalanced samples, which has been widely used in various fields of data mining. For example, it can help detect ...