Machine learning in manufacturing towards industry 4.0: From 'for now'to 'four-know'

T Chen, V Sampath, MC May, S Shan, OJ Jorg… - Applied Sciences, 2023 - mdpi.com
While attracting increasing research attention in science and technology, Machine Learning
(ML) is playing a critical role in the digitalization of manufacturing operations towards …

OralNet: fused optimal deep features framework for oral squamous cell carcinoma detection

R Mohan, A Rama, RK Raja, MR Shaik, M Khan… - Biomolecules, 2023 - mdpi.com
Humankind is witnessing a gradual increase in cancer incidence, emphasizing the
importance of early diagnosis and treatment, and follow-up clinical protocols. Oral or mouth …

CBAM VGG16: An efficient driver distraction classification using CBAM embedded VGG16 architecture

CH Praharsha, A Poulose - Computers in biology and medicine, 2024 - Elsevier
Driver monitoring systems (DMS) are crucial in autonomous driving systems (ADS) when
users are concerned about driver/vehicle safety. In DMS, the significant influencing factor of …

[HTML][HTML] Collaborative Intelligence for Safety-Critical Industries: A Literature Review

IF Ramos, G Gianini, MC Leva, E Damiani - Information, 2024 - mdpi.com
While AI-driven automation can increase the performance and safety of systems, humans
should not be replaced in safety-critical systems but should be integrated to collaborate and …

Enhanced Generalization Performance in Deep Learning for Monitoring Driver Distraction: A Systematic Review

K Dinakaran, F Kavin, P Anitha… - … in Applied Sciences …, 2024 - semarakilmu.com.my
Automatic analysis of driver behaviour is one of the most difficult subjects in the field of
intelligent transportation systems. This study focuses on disturbed driver stance identification …

Detection of distracted driving via edge artificial intelligence

D Chen, Z Wang, J Wang, L Shi, M Zhang… - Computers and Electrical …, 2023 - Elsevier
Real-time detection and alert systems for distracted driving are pivotal areas of research.
With Edge AI, it is feasible to process data in real-time without relying on Internet …

Hybrid Models Based on Fusion Features of a CNN and Handcrafted Features for Accurate Histopathological Image Analysis for Diagnosing Malignant Lymphomas

M Hamdi, EM Senan, ME Jadhav, F Olayah, B Awaji… - Diagnostics, 2023 - mdpi.com
Malignant lymphoma is one of the most severe types of disease that leads to death as a
result of exposure of lymphocytes to malignant tumors. The transformation of cells from …

U2-Net: A Very-Deep Convolutional Neural Network for Detecting Distracted Drivers

NO Alsrehin, M Gupta, I Alsmadi, SA Alrababah - Applied Sciences, 2023 - mdpi.com
In recent years, the number of deaths and injuries resulting from traffic accidents has been
increasing dramatically all over the world due to distracted drivers. Thus, a key element in …

Evaluation of 1D and 2D deep convolutional neural networks for driving event recognition

ÁT Escottá, W Beccaro, MA Ramírez - Sensors, 2022 - mdpi.com
Driving event detection and driver behavior recognition have been widely explored for many
purposes, including detecting distractions, classifying driver actions, detecting kidnappings …

Effective lane detection on complex roads with convolutional attention mechanism in autonomous vehicles

V Maddiralla, S Subramanian - Scientific Reports, 2024 - nature.com
Autonomous Vehicles (AV's) have achieved more popularity in vehicular technology in
recent years. For the development of secure and safe driving, these AV's help to reduce the …