IEEE

Enhancing CNN-Based Motion Sickness Detection using EEG Signals Weighted by Motion Sickness Dose Value

Abstract: With the advancement of autonomous driving technologies, passengers increasingly engage in non-driving activities. However, these activities are often limited by motion sickness (MS), which ...
IEEE

Multilevel Multimodal CNN–Transformer Fusion Network for Land Use and Land Cover Classification

Abstract: In remote sensing (RS), convolutional neural networks (CNNs) are well-recognized for their spatial–spectral feature extraction capabilities, whereas vision transformers (ViTs), which ...
IEEE

Improved Transformer Network Based on Multiscale Grouping Feature Fusion for Hyperspectral Image Classification

Abstract: In recent years, hyperspectral image classification methods based on convolutional neural networks and Transformer architectures have achieved remarkable success. However, existing ...
IEEE

AI-based Circuit Fault Detection and Classification using Python Simulation

Abstract: Electrical circuits play a vital role in industrial, automotive, and power systems, where even minor faults can lead to severe performance degradation or system failure. Traditional fault ...
IEEE

Cross-Domain Hyperspectral Image Classification via Mamba–CNN and Knowledge Distillation

Abstract: Domain adaptation (DA)-based cross-domain hyperspectral image (HSI) classification methods have garnered significant attention. The majority of DA techniques utilize models based on ...
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CNN poll: 56% believe Minneapolis ICE shooting was not appropriate use of force

CNN’s Harry Enten breaks down the numbers. Republican signals support for Trump impeachment 17 college basketball players charged in point-shaving scheme: Indictment I asked 3 restaurant pros to name ...
IEEE

Data-Free Backdoor Attack on Malware Image Classification Models

Abstract: Machine learning-based image malware classifiers are increasingly vital for safeguarding enterprises and infrastructure. However, these models are vulnerable to backdoor attacks, where ...
IEEE

Bone Fracture Classification Using Deep Learning Models with Transfer Learning

Abstract: Bone fracture can be defined as the complete or partial disruption of the integrity of bone tissue. Early and accurate diagnosis of fractures plays a decisive role in the effectiveness of ...
IEEE

An Ensemble Deep Learning Model Using CNN, LSTM and Autoencoder for EEG-Based Parkinson’s Disease Classification

Abstract: Parkinson's disease is a neurological disorder hat effects the movements including shaking, stiffness, difficulty while walking and speaking. This condition will occur when the nerve cells ...
IEEE

Implementation of Brain Tumor Detection and Classification Model Using CNN Approach

Abstract: Unless diagnosed and treated early, brain tumors unusual growths may prove to be lethal. Even with the standard methods, such as MRI scans, to precisely diagnose brain cancers, it may be ...
IEEE

Dynamic Beat-to-Beat Measurements of Blood Pressure Using Multimodal Physiological Signals and a Hybrid CNN-LSTM Model

Abstract: Wearable cuffless blood pressure (BP) technology is emerging as a critical tool for monitoring hypertension, the leading risk factor of most cardiovascular diseases. However, current ...
IEEE

Matching Street View Images for the Classification of Urban Land Use From Very-High-Resolution Remote Sensing Images

Abstract: Street view (SV) images provide valuable supplementary data for characterizing the functional attributes of land use types, improving urban land use classification based on ...