Res-DNN based signal detection algorithm for end-to-end MIMO systems by Guoquan LI, Yonghai XU, Jinzhao LIN, Zhengwen HUANG

“…Deep learning can improve the effect of signal detection by extracting the inherent characteristics of wireless communication data.To solve the tradeoff between the performance and complexity of MIMO system signal detection, an end-to-end MIMO system signal detection scheme based on deep learning was proposed.The encoder and the decoder based on residual deep neural network replace the transmitter and the receiver of the wireless communication system respectively, and they were trained in an end-to-end manner as a whole.Firstly, the features of the input data were extracted by encoder, then the communication model was established and was sent to the zero forcing detector for preliminary detection.Finally, the detection signal was reconstructed through the decoder.Simulation results show that the proposed detection scheme is superior to the same type of algorithm, and the detection performance is significantly better than that of the MMSE detection algorithm at the expense of a certain time complexity.…”
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Res-DNN based signal detection algorithm for end-to-end MIMO systems by Guoquan LI, Yonghai XU, Jinzhao LIN, Zhengwen HUANG

“…Deep learning can improve the effect of signal detection by extracting the inherent characteristics of wireless communication data.To solve the tradeoff between the performance and complexity of MIMO system signal detection, an end-to-end MIMO system signal detection scheme based on deep learning was proposed.The encoder and the decoder based on residual deep neural network replace the transmitter and the receiver of the wireless communication system respectively, and they were trained in an end-to-end manner as a whole.Firstly, the features of the input data were extracted by encoder, then the communication model was established and was sent to the zero forcing detector for preliminary detection.Finally, the detection signal was reconstructed through the decoder.Simulation results show that the proposed detection scheme is superior to the same type of algorithm, and the detection performance is significantly better than that of the MMSE detection algorithm at the expense of a certain time complexity.…”
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A review: Multi-Objective Algorithm for Community Detection in Complex Social Networks by Mariwan Wahid Ahmed, Kamaran Faraj

“…Recently, research on multi-objective optimization algorithms for community detection in complex networks has grown considerably. …”
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An edge detection method of pantograph carbon slide based on an improved Canny algorithm by YANG Jun, GUO Youmin, WANG Jianxin, ZHAO Hongliang

“…Aiming at the problems of inaccurate extraction, discontinuity and being susceptible to noise when the edge of a carbon slide is detected by using a traditional edge detection algorithm, an edge detection method of pantograph carbon slide based on an improved Canny algorithm was proposed in the paper. …”
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A Credit Card Fraud Detection Algorithm Based on SDT and Federated Learning by Yuxuan Tang, Zhanjun Liu

“…Thanks to the attention mechanism of the Transformer, the model can automatically highlight important features in the data, significantly improving the accuracy of fraud detection. …”
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Detecting Planting Holes Using Improved YOLO-PH Algorithm with UAV Images by Kaiyuan Long, Shibo Li, Jiangping Long, Hui Lin, Yang Yin

“…However, existing target detection algorithms face difficulties in identifying planting holes based on their edge features, particularly in complex environments. …”
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Soft detection model of corrosion leakage risk based on KNN and random forest algorithms by Yang YANG, Chengzhi LI, Xuan DU, Xiao YU, Shaohua DONG

“…These identified indicators were then employed to develop an intelligent soft detection model that integrates pipeline and environmental data, based on the K-Nearest Neighbor (KNN) and Random Forest algorithms. …”
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Classification of chest radiographs into healthy/pneumonia using Harris-Hawks Algorithm optimized deep-features by K. Vijayakumar, Mohammad Nazmul Hasan Maziz, Swaetha Ramadasan, Seifedine Kadry, S. Arunmozhi

“…Along with the traditional deep-features based classification using the SoftMax, this work also considered Harris-Hawks Algorithm (HHA) algorithm based features optimization and serial features integration to generate fused-features vector (FFV). …”
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SRM-YOLO for Small Object Detection in Remote Sensing Images by Bin Yao, Chengkun Zhang, Qingxiang Meng, Xiandong Sun, Xuyang Hu, Lu Wang, Xilai Li

“…In this paper, we introduce SRM-YOLO, a novel small object detection algorithm based on the YOLOv8 framework. …”
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Road Obstacle Detection Method Based on Improved YOLOv5 by Pengliu Tan, Zhi Wang, Xin Chang

“…To address these issues, an enhanced obstacle detection algorithm based on YOLOv5 (YOLOv5-EC3F) is proposed. …”
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Predictive modeling of adolescent suicidal behavior using machine learning: Key features and algorithmic insights by Priya Metri, Swetta Kukreja

“…Suicidal ideation prevalence among students is a growing concern that requires urgent attention.This review systematically analyzes 28 studies on the application of machine learning techniques for the early detection of suicidal ideation. Among these, Random Forest and SVM emerged as the most commonly used algorithms, featured in 35 % and 27 % of studies respectively. …”
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Intrusion Detection System to Advance Internet of Things Infrastructure-Based Deep Learning Algorithms by Hasan Alkahtani, Theyazn H. H. Aldhyani

“…The experimental results confirmed that the proposed framework based on deep learning algorithms for an intrusion detection system can effectively detect real-world attacks and is capable of enhancing the security of the IoT environment.…”
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Development of Machine Vision Algorithms for Radioactive Contaminated Targets Detection in Dynamic Radiation Scenarios by Amir Mohammad Beigzadeh, Hadi Ardiny

“…The algorithm combines the beam detection system's data and machine vision. …”
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Explainable and Interpretable Model for the Early Detection of Brain Stroke Using Optimized Boosting Algorithms by Yogita Dubey, Yashraj Tarte, Nikhil Talatule, Khushal Damahe, Prachi Palsodkar, Punit Fulzele

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A comparative assessment of machine learning models and algorithms for osteosarcoma cancer detection and classification by Amoakoh Gyasi-Agyei

“…Machine learning (ML) models trained on disease datasets are more effective in detection and classification than the conventional methods with hand-crafted features highly dependent on pathologists’ expertise. …”
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Voice pathology detection using machine learning algorithms based on different voice databases by Nurul Mu'azzah Abdul Latiff, Fahad Taha Al-Dhief, Nurul Fariesya Suhaila Md Sazihan, Marina Mat Baki, Nik Noordini Nik Abd. Malik, Musatafa Abbas Abbood Albadr, Ali Hashim Abbas

“…The proposed study uses the Mel-Frequency Cepstral Coefficient (MFCC) technique for extracting features from voices. The algorithms are assessed using many evaluation metrics such as accuracy, precision, sensitivity, specificity, F-measure, and G-mean. …”
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Survivor detection approach for post earthquake search and rescue missions based on deep learning inspired algorithms by Rajendrasinh Jadeja, Tapankumar Trivedi, Jaymit Surve

“…This paper presents a novel approach to survivor detection using a snake robot equipped with deep learning (DL) based object identification algorithms. …”
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Identification of Plasma Proteins Associated with Alzheimer's Disease Using Feature Selection Techniques and Machine Learning Algorithms by Zakaria Mokadem, Mohamed Djerioui, Bilal Attallah, Youcef Brik

“…We applied two feature selection methods, Sequential Backward Feature Selection (SBFS) and Analysis of Variance (ANOVA) to extract significant proteins from a dataset of 146  proteins. …”
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Enhancing feature selection for multi-pose facial expression recognition using a hybrid of quantum inspired firefly algorithm and artificial bee colony algorithm by Mu Panliang, Sanjay Madaan, Siddiq Ahmed Babikir Ali, Gowrishankar J., Ali Khatibi, Anas Ratib Alsoud, Vikas Mittal, Lalit Kumar, A. Johnson Santhosh

“…In order to evaluate the efficacy of the proposed QIFABC algorithm, feature selection is also conducted using QIFA, FA, and ABC algorithms. …”
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Adaptive Multi-Radar Anti-Bias Track Association Algorithm Based on Reference Topology Features by Shaoming Wei, Xuan Zhou, Jun Wang, Rui Pang, Xueqing Li, Qiang Liu

“…To address the track association problem in multi-radar systems, particularly the challenges posed by offset bias, this paper proposes an adaptive multi-radar anti-bias track association algorithm based on reference topological features (RETs) that achieves accurate association despite offset bias and radar missed detections. …”
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