IEEE

Optimizing CNN for IoT Anomaly Detection in 6G using Ant Lion Optimizer and Slime Mould Algorithm

Abstract: The fast spread of the Internet of Things (IoT) and the approaching deployment of 6G networks have presented hitherto unheard-of possibilities and problems in network security. IoT devices ...
IEEE

Hybrid Beamforming for 5G MIMO based on Deep Learning Algorithm

Abstract: Hybrid beamforming for massive MIMO systems has attracted much interest due to its potential in next-generation wireless communications. Conventional beamforming methods, such as Matched ...
Frontiers

Advancing Deep Learning Frameworks for Enhanced Cervical Cancer Diagnosis, Staging and Treatment

Cervical cancer detection and diagnosis are undergoing a transformation with the integration of advanced deep learning (DL) technologies. Despite ...
IEEE

An Order Dispatch Algorithm for Ride-Hailing Based on Quantum Annealing and Multi-Agent Reinforcement Learning

Abstract: The popularity of ride-hailing has grown significantly, making it one of the mainstream modes of transportation. Its core value and competitive advantage largely lie in the precise and ...
IEEE

Deploying Deep Learning for Real-Time Tsunami Monitoring: A CNN-LSTM Model for Sensor-Based Prediction

Abstract: Early detection of tsunamis is essential for disaster risk reduction and minimizing loss of life. This research introduces an advanced deep learning-based tsunami detection model that ...
IEEE

A Deep Learning Approach for Automated Image Captioning with CNN and LSTM Models

Abstract: Accurately describing a picture has turned out to be a crucial problem, and expert system researchers have always been interested in image captioning, sometimes referred to as characterizing ...
IEEE

Printed Circuit Board Surface Defect Inspection via YOLOv5 Deep Learning Algorithm

Abstract: Printed Circuit Boards (PCBs) surface defects produced during manufacturing process negatively impact the quality of products, which directly influences the stability and reliability of ...
IEEE

An Explainable Hybrid Deep Learning Framework for Network Intrusion Detection Using Feature-Guided CNN Models

Abstract: Cybersecurity risks have evolved in the linked digital terrain of today into more complex, frequent, and varied forms. Conventional intrusion detection systems sometimes find it difficult to ...
IEEE

Deep Learning for 5G Localization: Hybrid CNN-Transformer Approach in Accuracy Enhancement

Abstract: Accurate localization of user equipments (UEs) in 5G communication systems is critical for maintaining synchronization with the base stations and supporting emerging location-based services.
IEEE

Accelerating Meta-Learning with the Enhanced Reptile Algorithm for Rapid Adaptation in Neural Networks

Abstract: Reptile is an innovative meta-learning approach that improves the process of neural networks training across diverse tasks. Reptile differs from the preference gradient strategies. It ...
IEEE

Effectiveness of different neural networks on intelligent detection of transmission line external damages

Abstract: In power system, identifying and eliminating the risks of overhead transmission line external damages plays a crucial role in ensuring safe operation of the grid. Image recognition ...