Algorithm Improvement for Mobile Event Detection with Intelligent Tunnel Robots by Li Wan, Zhenjiang Li, Changan Zhang, Guangyong Chen, Panming Zhao, Kewei Wu

“…This paper proposes an improved algorithm based on YOLOv9 and DeepSORT for intelligent event detection in an edge computing mobile device using an intelligent tunnel robot. …”
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SIFT Feature-Based Video Camera Boundary Detection Algorithm by Lingqiang Kong

“…Aiming at the problem of low accuracy of edge detection of the film and television lens, a new SIFT feature-based camera detection algorithm was proposed. …”
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SSCANL decoder based joint iterative detection and decoding algorithm by Chongyang LIU, Rui GUO

“…In order to improve the receiver performance of the sparse code multiple access (SCMA) system based on polar codes, the cyclic redundancy check (CRC) aided joint iterative detection and decoding receiver scheme based on simplify soft cancellation list (SSCANL) decoder (C-JIDD-SSCANL) was proposed.A polar code decoder in the C-JIDD-SSCANL receiver used the SSCANL algorithm.In this algorithm, decoding node deletion technology was used to simplify L times of soft cancellation (SCAN) decoding required by soft cancellation list (SCANL) algorithm by deleting frozen bit nodes, then the computational process of soft information update between nodes was simplified, and the computational complexity of decoding algorithm was reduced.The simulation results show that the SSCANL algorithm can obtain the same performance as the SCANL algorithm, and its computational complexity is reduced compared with the SCANL algorithm.Compared with the joint iterative detection and decoding scheme based on SCAN decoder (JIDD-SCAN) and the CRC aided joint iterative detection and decoding scheme based on SCAN decoder (C-JIDD-SCAN), the performance of C-JIDD-SSCANL receiver scheme based on SSCANL decoder is improved by about 0.65 dB and 0.59 dB respectively when the bit error rate is 10^-4.…”
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Detection of Malicious Executables Using Rule Based Classification Algorithms by Neeraj Bhargava, Aakanksha Jain, Abhishek Kumar, Dac-Nhuong Le

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YOLO-Dynamic: A Detection Algorithm for Spaceborne Dynamic Objects by Haiying Zhang, Zhengyang Li, Chunyan Wang

“…This paper presents YOLO-Dynamic, a novel detection algorithm aimed at addressing the limitations of existing models, particularly in complex environments and small-object detection. …”
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Low-Complexity Detection Algorithms for Spatial Modulation MIMO Systems by Xinhe Zhang, Yuehua Zhang, Chang Liu, Hanzhong Jia

“…The ost-oy-MBS detector combines the detection order of ost-MBS and oy-MBS together. The algorithm analysis and experimental results show that the proposed detectors outstrip MBS with respect to the BER performance and the computational complexity.…”
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Underwater Object Detection Algorithm Based on an Improved YOLOv8 by Fubin Zhang, Weiye Cao, Jian Gao, Shubing Liu, Chenyang Li, Kun Song, Hongwei Wang

“…Due to the complexity and diversity of underwater environments, traditional object detection algorithms face challenges in maintaining robustness and detection accuracy when applied underwater. …”
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YOLO-MECD: Citrus Detection Algorithm Based on YOLOv11 by Yue Liao, Lerong Li, Huiqiang Xiao, Feijian Xu, Bochen Shan, Hua Yin

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Comparative analysis of machine learning algorithms for money laundering detection by Sunday Adeola Ajagbe, Simphiwe Majola, Pragasen Mudali

“…This research aimed to identify robust algorithms for detecting financial fraud. In the results notably, XGBoost shows an output of 1.0, 1.0, 1.0, 1.0, and 0.94 for accuracy, precision, recall, F1 score and AUC respectively to outperform other ML algorithms experimented in money laundering detection. …”
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Machine learning algorithm for the rapid and accurate detection of Plasmodium falciparum by Mr Andrew Hill

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An Effective Algorithm for Video-Based Parking and Drop Event Detection by Gang Li, Huansheng Song, Zheng Liao

“…The existing algorithms for detection require accurate modeling of the background, and most of them use the characteristics of two-dimensional images such as area to distinguish the type of the target. …”
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Machine Learning Algorithms for Retinal Image Analysis and Glaucoma Detection by Akhter Hussain Syed, Pratap Mohanrao Mohite, Sandip Eknathrao Ingle, Mohammad Waseem Ahmed Siddiqui, Zeeshan Raziuddin Mohammed

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An insulator target detection algorithm based on improved YOLOv5 by Bing Zeng, Zhihao Zhou, Yu Zhou, Dilin He, Zhanpeng Liao, Zihan Jin, Yulu Zhou, Kexin Yi, Yunmin Xie, Wenhua Zhang

“…Abstract Drone inspections are widely utilized in the detection of insulators in power lines. To address issues with traditional object detection algorithms, such as large parameter counts, low detection accuracy, and high miss rates, this paper proposes an insulator detection algorithm based on an improved YOLOv5 model. …”
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MF-YOLO: Mask Wearing Detection Algorithm for Dense Environments by Peng Wen, Zhengyi Yuan, Junhu Zhang, Haitao Li

“…To address the challenges of false positives and missed detections in face mask detection within dense environments, we propose the MF-YOLO face mask detection model. …”
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An Enhanced Image Segmentation Technique-Based on Motion Detection Algorithm by Zaid Sh. Bakr, Hamzah M. Marhoon, Ammar Alaythawy

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MGL-YOLO: A Lightweight Barcode Target Detection Algorithm by Yuanhao Qu, Fengshou Zhang

“…To address this issue, this paper proposes MGL-YOLO, a lightweight one-dimensional barcode detection network based on an improved YOLOv8, which aims to achieve a high detection accuracy at low computational cost. …”
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Blockchain smart contract vulnerability detection based on GR algorithm by WANG Deguang, SHAN Mengtao, LI Fengqi, TONG Ning

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Improved spectral clustering algorithm and its application in MCI detection by Jie XIANG, Dong-qin ZHAO

“…In order to detect mild cognitive impairment (MCI) using functional magnetic resonance imaging (fMRI)，a method based on fMRI clustering was proposed fMRI data were clustered to obtain the blood oxygen level dependence( BOLD) change model of MCI patients，then abnormal patterns were used to detect disease.The traditional spectral clustering algorithm needs to calculate all of the eigenvalue and eigenvector，so time and space complexity is higher.An improved spectral clustering method was proposed which modified the similar matrix construction method and the setting method of σ and k，and then this method was applied to clustering and detection of MCI patients.To verify the performance of the proposed method，the comparison of the clustering result，classification accuracy using traditional algorithm and Nyström is also done.The comparative experimental results show that the proposed method can get BOLD pattern more accurately，the accuracy of MCI detection is higher than the other two algorithms，and the time and space complexity are less than the traditional algorithm.…”
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Ripe Tomato Detection Algorithm Based on Improved YOLOv9 by Yan Wang, Qianjie Rong, Chunhua Hu

“…To ensure the accuracy of inspection results, You Only Look Once version 9 (YOLOv9) has been explored as a fruit detection algorithm. To tackle the challenge of identifying tomatoes and the low accuracy of small object detection in complex environments, we propose a ripe tomato recognition algorithm based on an enhanced YOLOv9-C model. …”
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Micro-blog topic detection algorithm based on topic model by Hua-jun HUANG, Jun-shan TAN, Jiao-hua QIN

“…Micro-blog data has the characteristic of real-time,volume,short-text,and noise-rich.So it is a challenge for the traditional topic detection technology.A novel micro-blog topic detection algorithm based on topic model was proposed.Firstly,the micro-blog data was expressed as text word matrix and word relation matrix.The topic word was extracted from the two vectors.Secondly,the topic model was obtained with clustering.Finally,the topic detection of micro-blog was obtained by clustering text and topic model.Experimental results show that the algorithm proposed can effectively detection the text topic,and with the best parameter group of precision,recall rate,F,and the value F is about 95%.…”
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