IEEE

Efficient Document Image Classification Using Deep Learning Enhance with CNN Architectures

Abstract: Document image classification has a significant difficulty for the retrieval of digital documents and systems management in recent years. The main goal of this study is to investigate the ...
IEEE

Parallel Forecasting of LEO Satellite Downlink Channels Using a CNN-Transformer Architecture

Abstract: Low Earth Orbit (LEO) satellite constellations have been widely recognized as a key component of sixth-generation (6G) wireless communications due to their great potential in enabling ...
IEEE

Optimizing 2D CNN Architectures for Tabular IoT Intrusion Data: A Comparative Study Using the BoT-IoT 2020 Dataset

Abstract: The increasing number of Internet-enabled devices has demonstrated the need to have accurate intrusion detection systems (IDSs). To address this, we adapt the structure of two-dimensional ...
IEEE

P4-INT-Based Network Intrusion Detection Method Using CNN-BiLSTM with Multi-Head Attention

Abstract: With the widespread use of Internet services, the risk of cyber attacks has increased significantly. Existing anomaly-based network intrusion detection systems suffer from slow processing ...
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

Facial Recognition for Locating Missing Child Using CNN Algorithm

Abstract: In India, countless children are reported missing every year, with a significant percentage remaining untraced due to challenges in identification and limited resources. This project ...
IEEE

Early Radar Work Mode Recognition Using Hybrid CNN-Transformer and Reinforcement Learning

In this paper, a novel approach is proposed for early recognition of Radar Work Mode, which integrates a hybrid CNN-Transformer architecture and a Reinforcement Learning strategy. The model processes ...
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

Self-Supervised Monocular Depth Estimation Using Hybrid CNN-VMamba Architecture

Abstract: Self-supervised monocular depth estimation (MDE) typically employs convolutional neural networks (CNNs) or Transformers to predict scene depth. However, CNNs struggle with long-range ...
IEEE

Automated Deep Learning System for Early Detection of Stroke Using CNN Architecture

Abstract: Strokes are a major cause of disability worldwide, with ischemic and hemorrhagic strokes accounting for the majority of cases. In India, stroke remains the second most common cause of ...
CNN

ICE shunned body cams in Minnesota. So why are agents using phone cameras?

From Chicago to Minneapolis, federal immigration agents deployed on Trump administration crackdowns have relied on an unlikely tool in the heat of tense operations — cellphone cameras. That practice ...
CNN

Trump just backed off on using military force to take Greenland. What does it mean?

President Donald Trump’s quest for control of Greenland took a significant turn on Wednesday, when he backed off on using military force — an option he and his team had previously reserved. Speaking ...