Monitoring and Analyzing Driver Physiological States Based on Automotive Electronic Identification and Multimodal Biometric Recognition Methods by Shengpei Zhou, Nanfeng Zhang, Qin Duan, Xiaosong Liu, Jinchao Xiao, Li Wang, Jingfeng Yang

Get full text

A Novel Equivariant Self-Supervised Vector Network for Three-Dimensional Point Clouds by Kedi Shen, Jieyu Zhao, Min Xie

Get full text

From Stationary to Nonstationary UAVs: Deep-Learning-Based Method for Vehicle Speed Estimation by Muhammad Waqas Ahmed, Muhammad Adnan, Muhammad Ahmed, Davy Janssens, Geert Wets, Afzal Ahmed, Wim Ectors

“…The process involves matching each pixel of the input frame with a georeferenced orthomosaic using a feature-matching algorithm. Subsequently, a tracking-enabled YOLOv8 object detection model is applied to the frame to detect vehicles and their trajectories. …”
Get full text

Enhancing deep convolutional neural network models for orange quality classification using MobileNetV2 and data augmentation techniques by Phan Thi Huong, Lam Thanh Hien, Nguyen Minh Son, Huynh Cao Tuan, Thanh Q. Nguyen

Get full text

Decoding Depression from Different Brain Regions Using Hybrid Machine Learning Methods by Qi Sang, Chen Chen, Zeguo Shao

“…Compared with traditional single methods, the hybrid approach significantly improved detection accuracy by leveraging the strengths of different algorithms. …”
Get full text

Detección y diagnóstico de fallas en motores mediante el análisis de vibraciones aplicando técnicas de inteligencia artificial. by Jair Elías Araujo Vargas, Dilan Yesid Franklin Coronel, Victor Manuel Arias Ruiz

“…Therefore, the performance of different artificial intelligence algorithms in the field of fault detection and diagnosis using vibration analysis in motors was evaluated. …”
Get full text

The Study of Roadside Visual Perception in Internet of Vehicles Based on Improved YOLOv5 and CombineSORT by LI Xiaohui, YANG Jie, XIA Qin

“…Compared to other commonly algorithms, this algorithm can simultaneously achieve higher detection accuracy and lower time cost for high volume intersections, offering good application prospects in vehicle road collaboration scenarios. …”
Get full text

Deep Learning in Visual Computing and Signal Processing by Danfeng Xie, Lei Zhang, Li Bai

“…In this study, we not only review typical deep learning algorithms in computer vision and signal processing but also provide detailed information on how to apply deep learning to specific areas such as road crack detection, fault diagnosis, and human activity detection. …”
Get full text

Evaluating Security Anomalies by Classifying Traffic Using a Multi-Layered Model by Mohammadreza Samadzadeh, Najmeh Farajipour Ghohroud

“…In this study, a two-step classification method based on deep learning algorithms is presented, which can achieve high classification accuracy without manually selecting and extracting features. …”
Get full text

A Mountain Summit Recognition Method Based on Improved Faster R-CNN by Yueping Kong, Yun Wang, Song Guo, Jiajing Wang

“…Traditional summit detection methods operate on handcrafted features extracted from digital elevation model (DEM) data and apply parametric detection algorithms to locate mountain summits. …”
Get full text

Analyzing mental stress in Indian students through advanced machine learning and wearable technologies by Shruti Gedam, Sandip Dutta, Ritesh Jha

“…Univariate feature analysis found that XGBoost regularly demonstrated good accuracy, showing its dependability for detecting mental stress. …”
Get full text

Monitoring Pine Wilt Disease Using High-Resolution Satellite Remote Sensing at the Single-Tree Scale with Integrated Self-Attention by Wenhao Lv, Junhao Zhao, Jixia Huang

“…This study introduces several advanced self-attention algorithms into the task of satellite-based monitoring of pine wilt disease to enhance detection performance. …”
Get full text

River Surface Space–Time Image Velocimetry Based on Dual-Channel Residual Network by Ling Gao, Zhen Zhang, Lin Chen, Huabao Li

“…However, environmental interference often blurs weak tracer textures in STIs, limiting the accuracy of traditional MOT detection algorithms based on shallow features like images’ gray gradient. …”
Get full text

Current status and outlook of UWB radar personnel localization for mine rescue by ZHENG Xuezhao, MA Jiawen, HUANG Yuan, LI Qiang, REN Jing, LIU Yu

“…Future research directions of UWB radar personnel localization technology for mine rescue operations are proposed: ① optimizing the UWB radar localization system by constructing cross-modal information fusion models and developing highly adaptive signal processing methods to enhance the system's adaptability to post-mining disaster environments; ② improving the applicability of combined static and dynamic target localization by developing hybrid localization algorithms that integrate Bayesian networks or deep belief networks to fuse static and dynamic target features and establishing state-switching-based comprehensive models; ③ improving UWB radar echo processing algorithms, combining adaptive beamforming technology, Multiple Input Multiple Output (MIMO) technology, and optimized K-means++ or entropy-based hierarchical analysis algorithms, effectively distinguishing multi-target position information, and validating their adaptability and reliability in complex environments through extensive simulation experiments.…”
Get full text

Recent Facial Image Preprocessing Techniques: A Review by Rendra Soekarta, Ku Ruhana Ku-Mahamud

“…Facial image preprocessing is a critical step in various applications, including facial recognition, emotion detection, and biometric authentication. Preprocessing methods including normalization, noise reduction, illumination correction, alignment, resolution enhancement, data augmentation, and edge detection are essential for improving image quality and standardizing facial features in improving facial image quality. …”
Get full text

Discovering Human Presence Activities with Smartphones Using Nonintrusive Wi-Fi Sniffer Sensors: The Big Data Prospective by Weijun Qin, Jiadi Zhang, Bo Li, Limin Sun

“…By deploying in the real-world office environment, we found that the performance of Wi-Fi messages aggregation of CAOCA and CACFA algorithms is over 3.8 times higher than the worst channel of FCA algorithms and about 76% of the best channel of FCA algorithms, and the human presence detection rate reached 87.4%.…”
Get full text

Tri-band vehicle and vessel dataset for artificial intelligence research by Yingjian Liu, Gangnian Zhao, Shuzhen Fan, Cheng Fei, Junliang Liu, Zhishuo Zhang, Liqian Wang, Yongfu Li, Xian Zhao, Zhaojun Liu

“…About 60% of the dataset has been manually labeled with object instances to train and evaluate well-established object detection algorithms. After training with YOLOv8 and SSD object detection algorithms, all models have mAP values above 0.6 at an IoU threshold of 0.5, which indicates good recognition performance for this dataset. …”
Get full text

Small traffic sign recognition method based on improved YOLOv7 by Bo Meng, Weida Shi

“…Abstract As autonomous and assisted driving technologies progress rapidly, the significance of traffic sign recognition intensifies. Currently, the detection accuracy of algorithms for traffic sign recognition remains suboptimal, particularly when identifying small traffic signs amid complex backgrounds and under inadequate lighting, leading frequently to errors in detection. …”
Get full text

Prediction of acute kidney injury in intensive care unit patients based on interpretable machine learning by Li Zhang, Mingyu Li, Chengcheng Wang, Chi Zhang, Hong Wu

“…Objective Acute kidney injury (AKI) poses a lethal risk in intensive care unit (ICU) patients, where early detection is challenging. This study was to establish a prediction model for AKI 24 hours in advance for ICU patients and to help clinicians monitor patients at an early stage by key features. …”
Get full text

Longitudinal Changes in Pitch-Related Acoustic Characteristics of the Voice Throughout the Menstrual Cycle: Observational Study by Jaycee Kaufman, Jouhyun Jeon, Jessica Oreskovic, Anirudh Thommandram, Yan Fossat

“…The analysis included comparisons of these features between the follicular and luteal phases and the application of changepoint detection algorithms to assess changes and pinpoint the day in which the shifts in vocal pitch occur. …”
Get full text