Research on Target-detection and Tracking of Intelligent Mine Trucks in Open-pit Mines by LI Yuanzhengyu, HU Yunqing, LONG Teng, HUANG Wenyu, PAN Wenbo, LI Peijie

“…To ensure the safety of mine trucks on unpaved roads and in dusty environments, it's necessary to improve the efficiency and robustness of targets detection and tracking. This paper proposes a multi-target detection and tracking algorithm based on the fusion of light detection and ranging (LiDAR) and millimeter-wave radar. …”
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An Optimization Algorithm for Forward-Scatter Radar Network Node Deployment Based on BFGS and Improved NSGA-II by Yuqing Zheng, Xiaofeng Ai, Zhiming Xu, Jing Wu, Feng Zhao

“…A multi-objective optimization model was subsequently established with the objective functions of minimizing node cost and maximizing spatial detection area. Second, a method based on the Broyden–Fletcher–Goldfarb–Shanno (BFGS) algorithm was introduced to obtain the sub-optimal solution of node cost, thereby reducing the computational complexity of the optimization process. …”
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BT-YOLO11: Automatic Driving Road Target Detection in Complex Scenarios by Qi Wang, Qi Long Wang

“…In order to solve this problem, a target detection algorithm for complex scenes BT-YOLO11 is proposed based on the latest YOLO11. …”
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A Method for Solving LiDAR Waveform Decomposition Parameters Based on a Variable Projection Algorithm by Ke Wang, Guolin Liu, Qiuxiang Tao, Luyao Wang, Yang Chen

“…To address this issue, we evaluated the structural characteristics of received LiDAR signals by decomposing them into Gaussian functions and applied the variable projection algorithm of the separable nonlinear least-squares problem to the process of waveform fitting. …”
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Study Comparison Deep Learning and Support Vector Machine for Face Mask Detection by Rani Kurnia Putri, Muhammad Athoillah*

“…Deep Learning works by representing data in layers of learning layers so that the representation becomes more meaningful, and Support Vector Machine tries to find the hyperplane that maximizes the margin between the hyperplane and the closest data points from each class so that the classification becomes more accurate. Both algorithms have proven to be powerful tools for any classification problem specially to classify or identify image patterns. …”
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Machine learning for Internet of things anomaly detection under low-quality data by Shangbin Han, Qianhong Wu, Yang Yang

“…However, the existing schemes ignore the problem of data quality, which leads to the unsatisfactory detection effect in practice. …”
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WMSNs Data Hidden Anomaly Detection Based on OH-KFJLT Bloom Filter by Chenkai Xiao, Zhongsheng Li, Yanming Wu

“…Sensors suffer from damage due to continuous high-load usage and wear, leading to anomalies in sensor data collected and recorded. To solve the problem, this paper proposes an anomaly detection algorithm that is based on the Bloom Filter model, combined with the Optimal Hyperplane-based Kronecker Fast Johnson-Lindenstrauss Transform (OH-KFJLT) mapping and Reciprocal Competition Strategy(RCS), called Optimal Hyperplane Kronecker Fast Johnson-Lindenstrauss Transform Bloom Filter Anomaly Detection(OFBFAD). …”
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Application of Artificial Intelligence for the Implementation of Mismatch Negativity Potential Algorithms in Industrial Automated Predictive Maintenance Systems by Alexander Yu. Chesalov

“…The basic architecture of the automated system is proposed, which takes into account the need to use software algorithms of mismatch negativity potential. It consists of modules of data verification, model training, anomaly detection, predictive model, visualization and module of integration with other industrial information and automated systems. …”
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Ship detection optimization method in SAR imagery based on multi-feature weighting by Quanhua ZHAO, Xiao WANG, Yu LI, Guanghui WANG

“…Aiming at the problem that the accuracy of traditional ship detection algorithms is not satisfying in complex scene with many false alarm targets,a ship detection optimization method in SAR imagery based on multi-feature weighting was proposed.Firstly,the marker-based watershed algorithm was employed to remove land from SAR amplitude image.Then,the CFAR algorithm based on log-normal distribution was used to obtain candidate targets from no land image.Furthermore,the length to width ratio,the ship area and the contrast ratio of the candidate targets were extracted.Finally,a variance coefficient method was proposed to distribute the weight of the three features,and the confidence levels were calculated by combining the normalized feature vectors of the candidate targets with the feature weight.By determining the best confidence level,false alarm targets among the candidate targets were removed to optimize ship detection results.In order to verify the proposed method,experiments were carried on with the GF-3 SAR images of different complex scenes.The experimental results show that the proposed method is feasible and effective.…”
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A feature-based intelligent deduplication compression system with extreme resemblance detection by Xiaotong Wu, Jiaquan Gao, Genlin Ji, Taotao Wu, Yuan Tian, Najla Al-Nabhan

“…We propose a content-defined chunking algorithm for duplicate detection and a Bloom filter-based resemblance detection algorithm. …”
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A Multiobjective Evolutionary Algorithm for Energy-Efficient Cooperative Spectrum Sensing in Cognitive Radio Sensor Network by Weirong Liu, Gaorong Qin, Shuo Li, Jian He, Xiaoyong Zhang

“…The main objective of the proposed algorithm is to minimize the network energy consumption subjected to constraints on the detection performance by optimally deriving the censoring and sleeping probabilities. …”
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Cumulative confidence-driven task offloading for object detection in maritime Internet of Things by Yanglong Sun, Wenqian Luo, Weijian Xu, Qiang Mei, Haixia Peng, Linhai Wei

“…The simulation results indicate that, compared to existing algorithms, the proposed SNAP-DDPG algorithm keeps object detection confidence, with latency reduced by 34.78%.…”
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Impact of Adaptive Synthetic on Naïve Bayes Accuracy in Imbalanced Anemia Detection Datasets by Muhammad Khahfi Zuhanda, Lisya Permata, Hartono, Erianto Ongko, Desniarti

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Event‐triggered attack detection and state estimation based on Gaussian mixture model by Lu Jiang, Di Jia, Jiping Xu, Cui Zhu, Kun Liu, Yuanqing Xia

“…Abstract Under the framework of event‐triggered transmission mechanism, the problem of attack detection and state estimation of multi‐sensor linear time‐invariant systems under static attacks is considered. …”
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Generate vector graphics of fine-grained pattern based on the Xception edge detection. by Anqi Chen, Yicui Peng, Meng Li, Hao Chen, Chang Liu, Jinrong Hu, Xiang Wen, Guo Huang

“…The use of the Xception algorithm effectively solves the problem of extraction of Qiang embroidery in two-dimensional vectorial images. …”
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Rail Corrugation Detection of High-Speed Railway Using Wheel Dynamic Responses by Jianbo Li, Hongmei Shi

“…The optimal parameters of EEMD are selected according to the orthogonal coefficient of decomposition results and the distribution of the extreme points of signal. The depth detection is transformed to a classification problem with SVM. …”
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Application of nine point logic control and predictive pid control algorithms in smart grid decision-making by Zhixin Ou

“…First, models and algorithms for smart grids, improve the multiple domain value delay problem of output stability. …”
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Adaptive Multiobjective Evolutionary Generative Adversarial Network for Metaverse Network Intrusion Detection by Dikai Xu, Bin Cao

“…Designing effective neural networks for intrusion detection algorithms relies heavily on expert experience, making the manual process time-consuming and often yielding suboptimal results. …”
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DMSF-YOLO: Cow Behavior Recognition Algorithm Based on Dynamic Mechanism and Multi-Scale Feature Fusion by Changfeng Wu, Jiandong Fang, Xiuling Wang, Yudong Zhao

“…Because of the complex background, multi-scale behavior changes of dairy cows, similar behavior, and difficulty in detecting small targets in the actual dairy farm environment, this study proposes a dairy cow behavior recognition algorithm, DMSF-YOLO, based on dynamic mechanism and multi-scale feature fusion, which can quickly and accurately identify the lying, standing, walking, eating, drinking and mounting behaviors of dairy cows. …”
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A Robust Home Alone Faint Detection Based on Wireless Sensor Networks by Zhen-hai Wang, Bo Xu

“…Target detection and tracking are one of the fundamental problems for wireless sensor networks and play an important role in the safety field. …”
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