YOLOv8-UCB: Visual Detection of Pouch Battery Using Improved YOLOv8 by Hao Hao, Xiang Yu

“…The aluminum laminate pouch of pouch batteries is highly prone to deformation, which can cause various surface defects, thereby affecting their service life and potentially posing safety hazards. To address this problem, we propose an algorithm named YOLOv8-UCB for detecting surface defects in pouch batteries, which is based on the YOLOv8 model. …”
Get full text

An Efficient Aircraft Conflict Detection and Resolution Method Based on an Improved Reinforcement Learning Framework by Qiucheng Xu, Zhangqi Chen, Fangfang Li, Zhiyuan Shen, Wenbin Wei

“…Three simulation scenarios were designed for illustrating the improvements of the proposed algorithm, with the results indicating that the algorithm could establish and maintain safe separation between 20 agents in the simplified hexagon-shaped airspace of Huadong, China. …”
Get full text

SAR ship target detection method based on CNN structure with wavelet and attention mechanism. by Shiqi Huang, Xuewen Pu, Xinke Zhan, Yucheng Zhang, Ziqi Dong, Jianshe Huang

“…To solve this problem, a new convolutional neural network (CNN) method based on wavelet and attention mechanism was proposed in this paper, called the WA-CNN algorithm. …”
Get full text

Research on detection and tracking methods of unmanned ship water targets based on light vision by LIU Yibo, QIU Xinyu, WANG Tianhao, GAOYAN Xiusong, WANG Yintao

“…This research demonstrates that in the field of surface unmanned ships, target detection and tracking problems can be effectively solved by integrating advanced image processing technology and machine learning algorithms.…”
Get full text

Safety belt wearing detection for electric aloft work based on EPSA-YOLOv5 by LI Yongfu, CHEN Libin, HUI Junwei, YUAN Runcong, CHAI Haokai

“…To address the problem of missed detection and slow detection speed in safety belt wearing test for electric aloft work, this paper proposed a method for detecting the wearing of safety belts based on EPSA-YOLOv5 algorithm. …”
Get full text

UAV Small Target Detection Model Based on Dual Branches and Adaptive Feature Fusion by Guogang Wang, Mingxing Gao, Yunpeng Liu

“…In order to solve the problem of small and dense targets in drone aerial images, a small target detection model based on dual branches and adaptive feature fusion is proposed. …”
Get full text

IOF-Tracker: A Two-Stage Multiple Targets Tracking Method Using Spatial-Temporal Fusion Algorithm by Hongbin Liu, Yongze Zhao, Peng Dong, Xiuyi Guo, Yilin Wang

“…However, issues such as occlusions, directional changes, or shape alterations can cause appearance variations, leading to detection and matching problems that in turn result in frequent ID switches. …”
Get full text

Adaptive Anomaly Detection in Network Flows With Low-Rank Tensor Decompositions and Deep Unrolling by Lukas Schynol, Marius Pesavento

“…Inspired by Bayesian approaches, we extend the model architecture to perform online adaptation to per-flow and per-time-step statistics, improving AD performance while maintaining a low parameter count and preserving the problem's permutation equivariances. To optimize the deep network weights for detection performance, we employ a homotopy optimization approach based on an efficient approximation of the area under the receiver operating characteristic curve. …”
Get full text

The Development of a Lightweight DE-YOLO Model for Detecting Impurities and Broken Rice Grains by Zhenwei Liang, Xingyue Xu, Deyong Yang, Yanbin Liu

“…A rice impurity detection algorithm model, DE-YOLO, based on YOLOX-s improvement is proposed to address the issues of small crop target recognition and the similarity of impurities in rice impurity detection. …”
Get full text

Onboard LiDAR–Camera Deployment Optimization for Pavement Marking Distress Fusion Detection by Ciyun Lin, Wenjian Sun, Ganghao Sun, Bown Gong, Hongchao Liu

“…Then, the LiDAR–camera deployment problem was mathematically formulated for pavement marking distress fusion detection. …”
Get full text

Full-diversity design criterion for multi-user STBC based on integer-forcing detection by Guoquan LI, Xiangyun ZHOU, Jinzhao LIN, Yongjun XU, Yu PANG, Jiacheng WANG

“…Multi-user space time block code systems have the problem of high decoding complexity.To ensure good system performance with low decoding complexity at the same time,low complexity integer-forcing (IF) detection algorithm was applied to multi-user space time block code.Then the upper bound of error probability for IF detection was derived by minimizing the equivalent noise power.To obtain good multi-user space time block code when decoded with IF detection,a full-diversity design criterion was proposed.It was proved that full diversity could be achieved if every user’s space time block code had property of non-vanishing singular value.Simulation result shows that the code gain is found related to the minimum singular value.…”
Get full text

Full-diversity design criterion for multi-user STBC based on integer-forcing detection by Guoquan LI, Xiangyun ZHOU, Jinzhao LIN, Yongjun XU, Yu PANG, Jiacheng WANG

“…Multi-user space time block code systems have the problem of high decoding complexity.To ensure good system performance with low decoding complexity at the same time,low complexity integer-forcing (IF) detection algorithm was applied to multi-user space time block code.Then the upper bound of error probability for IF detection was derived by minimizing the equivalent noise power.To obtain good multi-user space time block code when decoded with IF detection,a full-diversity design criterion was proposed.It was proved that full diversity could be achieved if every user’s space time block code had property of non-vanishing singular value.Simulation result shows that the code gain is found related to the minimum singular value.…”
Get full text

Face Detection Method based on Lightweight Network and Weak Semantic Segmentation Attention Mechanism by Xiaoyan Wu

“…K-means++ algorithm is employed to perform clustering analysis on YOLOv4 model prior frames in this paper, and smaller size prior frames are set to capture small face information to solve the missing detection problem of small face targets in scenes. …”
Get full text

Automatic detection of fake reviews at marketplaces using expert-based features and consumers’ reactions by A. N. Borodulina, E. V. Mikhalkova

Get full text

Intelligent Recognition and Parameter Estimation of Radar Active Jamming Based on Oriented Object Detection by Jiawei Lu, Yiduo Guo, Weike Feng, Xiaowei Hu, Jian Gong, Yu Zhang

“…The core idea of the method is to reformulate the jamming perception problem as an object detection task in computer vision, and we pioneer the application of oriented object detection to this problem, enabling simultaneous jamming classification and key parameter estimation. …”
Get full text

Passive indoor human daily behavior detection method based on channel state information by Xiaochao DANG, Yaning HUANG, Zhanjun HAO, Xiong SI

“…The daily behavior detection of indoor human based on CSI is developing rapidly in the field of WSN.At present,most of the research is still in the environment of 2.4 GHz,so the detection rate,robustness and overall performance still need to be improved.In order to solve this problem,a passive indoor human behavior detection method HDFi (Human Detection with Wi-Fi) based on CSI signal was proposed.The method was used to detect the indoor human daily behavior in a 5 GHz band environment,which was divided into three steps:data acquisition,data processing,feature extraction,online detection.Firstly,the experiment collected typical daily behavioral data in complex laboratory and relatively empty meeting room.Secondly,the amplitude and phase data with more obvious features were extracted and processed by low-pass filtering to obtain a set of stable and noise-free data,and then the fingerprint database was established effectively.Finally,in the real-time detection stage,the collected data features were classified by SVM algorithm to extract more stable eigenvalues,and a classification model of indoor human daily behavior detection was established,and then matched the data in the fingerprint database.The experimental results show that the proposed method has the characteristics of high efficiency,high precision and good robustness,and the method does not need any testing personnel to carry any electronic equipment,so it has high practicability.…”
Get full text

Fault detection for stochastic time-varying systems based on adaptive disturbance rejection observers by Wenli ZHANG, Anning LIU, Jiantao SHI

“…Industrial systems and equipment are inevitably affected by random disturbances, which can degrade the performance of nominal controllers and potentially lead to control algorithm failures and system instability. To effectively address control and fault detection challenges in complex systems, it is crucial to systematically analyze the impact of unknown disturbances. …”
Get full text

Vision-Based Detection, Localization, and Optimized Path Planning for Rebar Intersections in Automated Construction by Chengxiang Li, Weimin Zhang, Fangxing Li, Meijun Guo, Shicheng Fan

“…To achieve comprehensive site coverage and optimize operational efficiency, the path planning challenge is reformulated as a sequencing optimization problem of the identified intersections. We propose a greedy optimization algorithm that generates smooth, snake-like traversal paths in an efficient manner. …”
Get full text

Detecting cyber attacks in vehicle networks using improved LSTM based optimization methodology by C. Jayasri, V. Balaji, C. M. Nalayini, S. Pradeep

“…To address this problem, this study proposes an enhanced deep learning-based optimization framework for detecting cyberattacks in vehicle networks. …”
Get full text

Remote Sensing Image Change Detection Based on Multi-Level Diversity Feature Fusion by Honggang Xie, Wanjie Ma

“…Secondly, to enhance the discrimination between change and unchanged regions during feature extraction and improve the utilization of feature extraction information, a Diversity Feature Fusion Module (DFFM) is designed to reduce false alarms and omissions in the detection results. Furthermore, to effectively address the problem of boundary misjudgment in change areas caused by fixed thresholds, an Adaptive Threshold Module is devised to adaptively learn the texture features of change and unchanged regions, enabling the generation of more accurate thresholds for boundary determination, thereby improving the robustness of the algorithm model and alleviating false alarms. …”
Get full text