Improved faster R-CNN for steel surface defect detection in industrial quality control by Yuefeng Leng, Jiazhi Liu

“…To address challenges including missed detections and low accuracy for fine defects, this study develops an enhanced Faster R-CNN algorithm. …”
Get full text

A Novel Method for Estimating Parameters of Magnetic Dipole Sources Under Low Signal-to-Noise Ratio Conditions Based on LM-OBF Algorithm by Zhaotao Yan, Zhaofa Zeng, Jianwei Zhao

Get full text

Reduced phase-state detection based on virtual modulation indexes for Multi-h CPM by Shunqin XIE, Ke ZHOU, Dahai CHEN, Xianglu LI, Sheng ZHONG, Jian ZHANG

Get full text

Two-Step Adaptive Target Detection Scheme Using Beam-Steering FMCW Radar Sensors by Bong-seok Kim, Young-seok Jin, Jieun Bae, Eugin Hyun

Get full text

Method on intrusion detection for industrial internet based on light gradient boosting machine by Xiangdong HU, Lingling TANG

“…Intrusion detection is a critical security protection technology in the industrial internet, and it plays a vital role in ensuring the security of the system.In order to meet the requirements of high accuracy and high real-time intrusion detection in industrial internet, an industrial internet intrusion detection method based on light gradient boosting machine optimization was proposed.To address the problem of low detection accuracy caused by difficult-to-classify samples in industrial internet business data, the original loss function of the light gradient boosting machine as a focal loss function was improved.This function can dynamically adjust the loss value and weight of different types of data samples during the training process, reducing the weight of easy-to-classify samples to improve detection accuracy for difficult-to-classify samples.Then a fruit fly optimization algorithm was used to select the optimal parameter combination of the model for the problem that the light gradient boosting machine has many parameters and has great influence on the detection accuracy, detection time and fitting degree of the model.Finally, the optimal parameter combination of the model was obtained and verified on the gas pipeline dataset provided by Mississippi State University, then the effectiveness of the proposed mode was further verified on the water dataset.The experimental results show that the proposed method achieves higher detection accuracy and lower detection time than the comparison model.The detection accuracy of the proposed method on the gas pipeline dataset is at least 3.14% higher than that of the comparison model.The detection time is 0.35s and 19.53s lower than that of the random forest and support vector machine in the comparison model, and 0.06s and 0.02s higher than that of the decision tree and extreme gradient boosting machine, respectively.The proposed method also achieved good detection results on the water dataset.Therefore, the proposed method can effectively identify attack data samples in industrial internet business data and improve the practicality and efficiency of intrusion detection in the industrial internet.…”
Get full text

YOLO-EFM: Efficient traffic flow monitoring algorithm with enhanced multi-level information fusion by Shizhou Xu, Kaidi Cui

“…Modern drones are capable of autonomously and efficiently collecting traffic images in complex environments to implement downstream detection tasks. However, existing object detection algorithms face challenges in recognizing blurred targets and detecting multi-scale objects. …”
Get full text

Real-time Detection and Tracking for Operating Vehicles in Complex Mining Environments by KANG Gaoqiang, LIN Jun, LIU Shiwang, YUE Wei, XIONG Qunfang, TONG Hao

“…Aiming at the problems of poor detection effect and low tracking stability of multi-type vehicles in complex mining environment due to the similarity of operating vehicles and background images, this paper proposes a multi-category and multi-target real-time detection and tracking algorithm for operating vehicles in complex mining environments. …”
Get full text

Research on Cam–Kalm Automatic Tracking Technology of Low, Slow, and Small Target Based on Gm-APD LiDAR by Dongfang Guo, Yanchen Qu, Xin Zhou, Jianfeng Sun, Shengwen Yin, Jie Lu, Feng Liu

“…With the wide application of UAVs in modern intelligent warfare as well as in civil fields, the demand for C-UAS technology is increasingly urgent. Traditional detection methods have many limitations in dealing with “low, slow, and small” targets. …”
Get full text

A method for detecting the rate of tobacco leaf loosening in tobacco leaf sorting scenarios by Yansong Wang, Yansong Wang, Chunjie Zhang, Chunjie Zhang, Mingjie Wu, Mingjie Wu, Ruilin Luo, Lin Lu, Zaiqing Chen, Zaiqing Chen, Lijun Yun, Lijun Yun

“…Additionally, a loss function with a monotonic focusing mechanism was introduced to increase the model’s learning capacity for difficult samples, resulting in a YOLO-TobaccoStem model more suitable for detecting tobacco stem objects. Lastly, a tobacco leaf loosening rate detection algorithm was formulated. …”
Get full text

Research on Abnormal Ship Brightness Temperature Detection Based on Infrared Image Edge-Enhanced Segmentation Network by Xiaobin Hong, Guanqiao Chen, Yuanming Chen, Ruimou Cai

“…Infrared imaging is based on thermal radiation and does not rely on visible light, allowing for it to operate normally at night and in low-light conditions. This characteristic is beneficial for regulatory authorities to monitor ships. …”
Get full text

BICLUSTERING APPLICATION IN INDONESIAN ECONOMIC AND PANDEMIC VULNERABILITY by Wiwik Andriyani Lestari Ningsih, I Made Sumertajaya, Asep Saefuddin

Get full text

ALGORITHM OF SIGNAL PROCESSING IN THE RADAR SYSTEM WITH CONTINUOUS FREQUENCY MODULATED RADIATION FOR DETECTION OF SMALL-SIZED AERIAL OBJECTS, ESTIMATION OF THEIR RANGE AND VELOCITY by I. F. Kupryashkin, N. V. Sokolik

“…The proposed algorithm of radar signals processing enables to simplify the detection of such tar-gets. …”
Get full text

Enhanced Adaptive Sine Multi-Taper Power Spectral Density Estimation for System Performance Evaluation in Low-Frequency Gravitational Wave Detection by Caiyun Liu, Yang Li, Changkang Fu, Hongming Zhang, Qiang Wang, Dong He, Yongmei Huang

“…The power spectral density estimation algorithms, logarithmic frequency axis for power spectral density (LPSD), and the LISA-LPSD algorithm are widely utilized in the implementation of system evaluations for space-based gravitational-wave-detection projects, particularly in the low-frequency band ranging from 0.1 mHz to 1 Hz. …”
Get full text

Metaheuristic Optimized Edge Detection for Recognition of Concrete Wall Cracks: A Comparative Study on the Performances of Roberts, Prewitt, Canny, and Sobel Algorithms by Nhat-Duc Hoang, Quoc-Lam Nguyen

“…Manual survey is notorious for low productivity. This study is aimed at establishing an image processing-based method for detecting cracks on concrete wall surfaces in an automatic manner. …”
Get full text

Application of microscopic image processing and artificial intelligence detecting and classifying the spores of three novel species of Trichoderma by Fatemeh Soltani Nezhad, Kamran Rahnama, Seyed Mohamad Javidan, Keyvan Asefpour Vakilian

“…Besides, the findings reveal that instead of deep learning-based methods which require big data for training, traditional feature extraction methods still provide promising results with low computational complexities. The use of such new techniques can help control plant diseases more effectively by providing faster and more accurate detection of Trichoderma spores in crop plants.…”
Get full text

Superior terahertz radiation detection through novel micro circular log-periodic antenna engineered with an advanced evolutionary neural network algorithm by Rui Zhou, Jiaqi Wang, Zhemiao Xie, Yonghai Sun, Guanxuan Lu, John T. W. Yeow

“…Abstract In this work, we introduce a novel Micro Circular Log-Periodic Antenna (MCLPA) optimized with an advanced Evolutionary Neural Network (ENN) algorithm, specifically designed to enhance terahertz (THz) radiation detection. …”
Get full text

Image Segmentation Based on the Optimized K-Means Algorithm with the Improved Hybrid Grey Wolf Optimization: Application in Ore Particle Size Detection by Xinyi Chai, Zijun Wu, Wei Li, Haowei Fan, Xinyang Sun, Jing Xu

“…Due to the poor quality and low efficiency of ore particle image segmentation in ore size detection, developing a fast and accurate algorithm for segmenting ore particle images remains a global challenge. …”
Get full text

D³-YOLOv10: Improved YOLOv10-Based Lightweight Tomato Detection Algorithm Under Facility Scenario by Ao Li, Chunrui Wang, Tongtong Ji, Qiyang Wang, Tianxue Zhang

“…However, under the facility scenario, existing detection algorithms still have challenging problems such as weak feature extraction ability for occlusion conditions and different fruit sizes, low accuracy on edge location, and heavy model parameters. …”
Get full text

WTI-SLAM: a novel thermal infrared visual SLAM algorithm for weak texture thermal infrared images by Sen Li, Xiaofei Ma, Rui He, Yuanrui Shen, He Guan, Hezhao Liu, Fei Li

“…Abstract This study addresses the challenges of robotic localization and navigation in visually degraded environments, such as low illumination and adverse weather conditions, by proposing a novel thermal infrared visual SLAM (Simultaneous Localization and Mapping) algorithm. …”
Get full text

Detection of Damage on Inner and Outer Races of Ball Bearings Using a Low-Cost Monitoring System and Deep Convolution Neural Networks by Handeul You, Dongyeon Kim, Juchan Kim, Keunu Park, Sangjin Maeng

Get full text