Machine learning and deep learning techniques for driver fatigue and drowsiness detection: a review
There are several factors for vehicle accidents during driving such as drivers' negligence,
drowsiness, and fatigue. These accidents can be avoided, if drivers are warned in time …
drowsiness, and fatigue. These accidents can be avoided, if drivers are warned in time …
A survey of multi-source image fusion
R Li, M Zhou, D Zhang, Y Yan, Q Huo - Multimedia Tools and Applications, 2024 - Springer
Multi-source image fusion has become an important and useful new technology in the image
understanding and computer vision fields. The purpose of multi-source image fusion is to …
understanding and computer vision fields. The purpose of multi-source image fusion is to …
LCD-capsule network for the detection and classification of lung cancer on computed tomography images
Lung cancer is the second most prominent cancer in men and women, and it is also the
leading cause of cancer-related mortality. If lung cancer is diagnosed early, when it is …
leading cause of cancer-related mortality. If lung cancer is diagnosed early, when it is …
A comparative analysis of classical machine learning and deep learning techniques for predicting lung cancer survivability
Lung cancer, one of the deadliest forms of cancer, can significantly improve patient survival
rates by 60–70% if detected in its early stages. The prediction of lung cancer patient survival …
rates by 60–70% if detected in its early stages. The prediction of lung cancer patient survival …
A novel machine learning based technique for classification of early-stage alzheimer's disease using brain images
Alzheimer's disease (AD) is a globally alarming neuro-degenerative abnormality for elderly
people. The earliest afflicted regions in AD are the brain tissues that form memory and other …
people. The earliest afflicted regions in AD are the brain tissues that form memory and other …
A fully streaming big data framework for cyber security based on optimized deep learning algorithm
Real-time deep learning faces the challenge of balancing accuracy and time, especially in
cybersecurity where intrusion detection is crucial. Traditional deep learning techniques have …
cybersecurity where intrusion detection is crucial. Traditional deep learning techniques have …
Real-time detection algorithm of marine organisms based on improved YOLOv4-Tiny
Y Shi, Z Gao, S Li - IEEE Access, 2022 - ieeexplore.ieee.org
Marine organisms detection based on machine vision requires high real-time performance
and accuracy. Network feature extraction is frequently made more difficult when underwater …
and accuracy. Network feature extraction is frequently made more difficult when underwater …
[PDF][PDF] A framework for robust attack detection and classification using rap-densenet
Network attacks must be effectively identified and categorized to guarantee strong security.
However, current techniques frequently have trouble correctly identifying and categorizing …
However, current techniques frequently have trouble correctly identifying and categorizing …
An intrusion system for internet of things security breaches using machine learning techniques
Effective identification and categorization of network attacks are paramount for ensuring
robust security. However, contemporary techniques often struggle to accurately discern and …
robust security. However, contemporary techniques often struggle to accurately discern and …
Fusion pose guidance and transformer feature enhancement for person re-identification
S Zhou, W Zou - Multimedia Tools and Applications, 2024 - Springer
Abstract In spite of Convolutional Neural Network (CNN) has dominated in the area of
Person Re-Identification, Transformer-based methods have emerged with their advantages …
Person Re-Identification, Transformer-based methods have emerged with their advantages …