An Intrusion Detection System Based on Deep Learning and Metaheuristic Algorithm for IOT by Bahman Sanjabi, Mahmood Ahmadi

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Massive MIMO signal detection based on approximate message passing algorithm by Chuang QIN, Ziwei ZHENG, Daping LOU, Xianzu FU

“…Massive multiple-input multiple-output(MIMO)brings huge improvements in energy efficiency and reduces emission power by using a large number of antennas,which is known as a key technology in the fifth generation (5G)mobile communication.With the increasing number of antennas,the complexity of signal detection is increasing at the same time.According to the research status of massive MIMO signal detection,approximate message passing algorithm was proposed.The complexity of AMP was compared to some iteration algorithm like Richarson algorithm and Neumann series approximation algorithm.The results indicate that the proposed algorithm can use less iteration to achieve almost the same performance of MMSE algorithm.…”
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Designing an algorithm to detect depression in users: A quantitative correlational study. by Hodan, T.

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ANALYZING EEG SIGNALS FOR STRESS DETECTION USING RANDOM FOREST ALGORITHM by Fi Imanur Sifaunnufus Ms, Fitra Abdurrachman Bachtiar, Barlian Henryranu Prasetio

“…Detection of stress using EEG signals has gained much interest because of monitoring and early intervention. …”
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Deep Learning Multi-Modal Melanoma Detection: Algorithm Development and Validation by Nithika Vivek, Karthik Ramesh

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An Anomaly Detection Based on Data Fusion Algorithm in Wireless Sensor Networks by Xingfeng Guo, Dianhong Wang, Fenxiong Chen

“…However, energy consumption and outlier detection have been always the hot topics in WSN. In order to solve the above problems, this paper proposes a timely anomaly detection algorithm which is based on the data fusion algorithm. …”
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Research on Traffic Marking Segmentation Detection Algorithm Based on Feature Fusion by Zhonghe He, Zizheng Gan, Pengfei Gong, Min Li, Kailong Li

“…However, road traffic markings are interfered with by a variety of factors, such as being obscured and the viewpoint of the vehicle sensors, resulting in large errors in the existing detection methods. In order to make the target detection task applicable to irregular objects or to detection tasks with higher accuracy requirements while reducing the waste of computational resources, this paper improves the accuracy of traffic marking segmentation detection by designing a multi-type traffic marking segmentation detection model based on image segmentation algorithms and designing a segmentation guidance matrix module based on a rank guidance matrix computation method. …”
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Barefoot Footprint Detection Algorithm Based on YOLOv8-StarNet by Yujie Shen, Xuemei Jiang, Yabin Zhao, Wenxin Xie

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Vision-based detection algorithm for monitoring dynamic change of fire progression by Yongyoon Suh

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Advanced Methodology for Fraud Detection in Energy Using Machine Learning Algorithms by Silviu Gresoi, Grigore Stamatescu, Ioana Făgărășan

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CGDINet: A Deep Learning-Based Salient Object Detection Algorithm by Chengyu Hu, Jianxin Guo, Hanfei Xie, Qing Zhu, Baoxi Yuan, Yujie Gao, Xiangyang Ma, Jialu Chen, Juan Tian

“…Salient object detection (SOD) is a key preprocessing step in computer vision, widely used in object tracking, action recognition, and image retrieval, among other fields. …”
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Low-Complexity Saliency Detection Algorithm for Fast Perceptual Video Coding by Pengyu Liu, Kebin Jia

“…A low-complexity saliency detection algorithm for perceptual video coding is proposed; low-level encoding information is adopted as the characteristics of visual perception analysis. …”
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Detection of Hydrophobicity Grade of Composite Insulators Based on MDC‐YOLO Algorithm by Shaotong Pei, Weiqi Wang, Chenlong Hu, Haichao Sun, Keyu Li, Mianxiao Wu, Bo Lan

“…Therefore, this paper proposes a MDC‐YOLO algorithm for water repellency detection and classification of composite insulators. …”
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On-board Multi-User Detection Algorithm Based on Conditional Neural Process by Yilun LIU, Liang JIN, Jiali LI, Lidong ZHU

“…With the characteristics of all-terrain, all-weather and seamless coverage, satellite communications have become a potentially important part of 6G.An important prerequisite for achieving satellite intelligence is that the satellite have on-board processing capabilities.Multi-user detection (MUD) is a classic method of suppressing multiple access interference (MAI) in wireless communication, such as MMSE, Gaussian processregression (GPR) and other algorithms.Due to the inverse matrix required in the detection process, the algorithm complexity is usually cubic, and it is diff cult to directly apply to satellite platforms because of its limited processing capabilities.The conditional neural process combined the characteristics of the low complexity of the neural network and the data-eff cient of the Gaussian process.The neural network was used to parameterized the Gaussian process to avoided the inversion of the matrix, thereby reduced the computational complexity.The application of conditional neural process in MUD was studied.The simulation results showed that, while reduced complexity, conditional neural process also greatly improved the performance of bit error rate (BER).…”
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A Closed-loop Detection Algorithm Based on Dynamic Time Warping by ZHU Tian, PENG Zhichuan, ZHANG Zhiteng, ZHU Zemin, XIE Yongbo, WANG Wenming

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Retracted: Multiobject Detection Algorithm Based on Adaptive Default Box Mechanism by null Complexity

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Comparisons of performances of structural variants detection algorithms in solitary or combination strategy. by De-Min Duan, Chinyi Cheng, Yu-Shu Huang, An-Ko Chung, Pin-Xuan Chen, Yu-An Chen, Jacob Shujui Hsu, Pei-Lung Chen

“…Numerous algorithms for short-read SV detection exist, but none are universally optimal, each having limitations for specific SV sizes and types. …”
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Video inter-frame tampering detection algorithm fusing multiple features by Hui XIAO, Bin WENG, Tianqiang HUANG, Han PU, Zehui HUANG

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Adaptive Cooperative Search Algorithm for Air Pollution Detection Using Drones by Il-kyu Ha

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Road Event Detection and Classification Algorithm Using Vibration and Acceleration Data by Abiel Aguilar-González, Alejandro Medina Santiago

“…In this work, we propose a Random Forest-based event classification algorithm designed to handle the unique patterns of vibration and acceleration data in road event detection for an urban traffic scenario. …”
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