5 December 2024

Integrating lightweight YOLOv5s and facial 3D keypoints for enhanced fatigued-driving detection

"The paper proposes a system for enhanced fatigued-driving detection by integrating the lightweight YOLOv5s model and facial 3D keypoints analysis. YOLOv5s, a real-time object detection model, is used to identify and track drivers’ faces efficiently. Meanwhile, 3D facial keypoints are employed to capture critical facial features. By combining these techniques, the system aims to improve the accuracy and speed of detecting fatigue-related behaviors in drivers, enhancing road safety by providing timely alerts to prevent accidents caused by drowsiness."

Carlos Fernandez-Lozano, Section Editor

3 December 2024

LOGIC: LLM-originated guidance for internal cognitive improvement of small language models in stance detection

"This study improves stance detection by leveraging large language models (LLMs) to deliver more comprehensive and precise insights compared to traditional methods. By using reasoning distillation, it transfers the capabilities of LLMs to smaller models, enabling efficient and high-quality stance detection on devices with limited resources."

Carlos Fernandez-Lozano, Section Editor

21 November 2024

A transformer-based framework for enterprise sales forecasting

"Transformer-based model for sales forecasting, helping decision-making in business operations."

Carlos Fernandez-Lozano, Section Editor

13 November 2024

Simulation methods realized by virtual reality modeling language for 3D animation considering fuzzy model recognition

"An insightful exploration of how virtual reality modeling language (VRML) can be effectively utilized for 3D animation, particularly in the context of fuzzy model recognition. The integration of simulation methods with VRML opens up new possibilities for creating more intuitive and responsive animations. This work is a significant contribution to the field, offering both theoretical and practical advancements. The approach to incorporating fuzzy logic into model recognition is especially commendable, as it enhances the adaptability and realism of virtual environments."

Carlos Fernandez-Lozano, Section Editor

13 November 2024

Novel statistically equivalent signature-based hybrid feature selection and ensemble deep learning LSTM and GRU for chronic kidney disease classification

"The article proposes an innovative hybrid method combining statistically equivalent signature-based feature selection with ensemble deep learning models (LSTM and GRU) to significantly improve the accuracy and efficiency of chronic kidney disease classification, addressing challenges in medical diagnostics with advanced machine learning techniques."

Carlos Fernandez-Lozano, Section Editor

11 November 2024

Unsupervised learning analysis on the proteomes of Zika virus

"Unsupervised learning analysis of omic data from virus, cross-discipline research."

Carlos Fernandez-Lozano, Section Editor

4 November 2024

Automatic visual recognition for leaf disease based on enhanced attention mechanism

"New applications of Deep Learning for visual recognition applied for leaf disease detection."

Carlos Fernandez-Lozano, Section Editor

4 November 2024

Generative named entity recognition framework for Chinese legal domain

"The study brings solid and interesting results, using deep learning for NER from legal domain"

Carlos Fernandez-Lozano, Section Editor

25 October 2024

Enhancing dance education through convolutional neural networks and blended learning

"Novel approaches of convolutional neural networks and blended learning to enhance dance education"

Carlos Fernandez-Lozano, Section Editor

18 October 2024

Pre-trained quantum convolutional neural network for COVID-19 disease classification using computed tomography images

"This article is crucial as it introduces a groundbreaking application of quantum convolutional neural networks (QCNN) to medical imaging, with a focus on quickly identifying COVID-19 from CT scans. The importance of this research lies in its potential to significantly boost diagnostic accuracy and efficiency during a global health emergency, addressing one of the most critical issues in healthcare today."

Carlos Fernandez-Lozano, Section Editor