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6661
AGW-YOLO-Based UAV Remote Sensing Approach for Monitoring Levee Cracks
Published 2025-01-01“…The advanced WIoUv3 loss function further boosted the model's performance, achieving a mAP@0.5 of 84.5% and an F1 score of 83%, marking an approximate 3.4% improvement over the baseline, and showcasing a favorable balance between detection accuracy and model efficiency. …”
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6662
Efficiency Design of Traction Inverters Based on Deep Learning and TRIZ
Published 2022-12-01“…In addition, this paper designs human-computer interaction software based on TRIZ-CRNN to improve the operation intelligence of computer aided innovation system and optimize the application feasibility of TRIZ-CRNN algorithm.…”
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6663
An Efficient Design of DCT Approximation Based on Quantum Dot Cellular Automata (QCA) Technology
Published 2019-01-01“…Optimization for power is one of the most important design objectives in modern digital image processing applications. …”
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6664
VR interactive input system based on INS and binocular vision fusion
Published 2024-12-01“…This study explores the application of inertial measurement units and binocular vision fusion technology in virtual reality interactive input systems, with the aim of improving the tracking accuracy of the system through optimized pose models and visual algorithms. …”
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6665
Machine learning based assessment of hoarseness severity: a multi-sensor approach centered on high-speed videoendoscopy
Published 2025-06-01“…Subjects were classified into two hoarseness groups based on auditory-perceptual ratings, with predicted scores serving as continuous hoarseness severity ratings. A videoendoscopic model was developed by selecting a suitable classification algorithm and a minimal-optimal subset of glottal parameters. …”
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6666
IoT intrusion detection method for unbalanced samples
Published 2023-02-01“…In recent years, network traffic increases exponentially with the iteration of devices, while more and more attacks are launched against various applications.It is significant to identify and classify attacks at the traffic level.At the same time, with the explosion of Internet of Things (IoT) devices in recent years, attacks on IoT devices are also increasing, causing more and more damages.IoT intrusion detection is able to distinguish attack traffic from such a large volume of traffic, secure IoT devices at the traffic level, and stop the attack activity.In view of low detection accuracy of various attacks and sample imbalance at present, a random forest based intrusion detection method (Resample-RF) was proposed, which consisted of three specific methods: optimal sample selection algorithm, feature merging algorithm based on information entropy, and multi-classification greedy transformation algorithm.Aiming at the problem of unbalanced samples in the IoT environment, an optimal sample selection algorithm was proposed to increase the weight of small samples.Aiming at the low efficiency problem of random forest feature splitting, a feature merging method based on information entropy was proposed to improve the running efficiency.Aiming at the low accuracy problem of random forest multi-classification, a multi-classification greedy transformation method was proposed to further improve the accuracy.The method was evaluated on two public datasets.F1 reaches 0.99 on IoT-23 dataset and 1.0 on Kaggle dataset, both of which have good performance.The experimental results show that the proposed model can effectively identify the attack traffic from the massive traffic, better prevent the attack of hackers on the application, protect the IoT devices, and thus protect the related users.…”
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6667
Design of Low-Power, High-Precision, and Lightweight Image Recognition System for Multiple Scenes
Published 2025-01-01“…Aiming at the existing handwritten digit recognition systems with low recognition accuracy, high system power consumption, and high hardware resource consumption, this paper proposes a low-power, high-precision, and lightweight handwritten digit recognition hardware acceleration scheme for multiscenario based on FPGA. By optimizing the network structure of a convolutional neural network (CNN) and the number of parameters of the model, this scheme proposes a high-precision and lightweight network model, simplified CNN, and by optimizing the data access mode and memory usage, and by adopting the strategies of time-sharing and multiplexing, weights sharing, and parallel processing for the hardware acceleration of the algorithm, it effectively reduces the consumption of hardware resources and improves the performance of the system. …”
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6668
Research on Status Assessment and Operation and Maintenance of Electric Vehicle DC Charging Stations Based on XGboost
Published 2024-10-01“…The training sample data are established using historical data, online monitoring data, and external environmental data, and the charging station status evaluation model is trained using the XGBoost algorithm. Based on the condition assessment results, a risk assessment model is established in combination with fault parameters. …”
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6669
A longan-picking sequence planning method for UAV system based on multi-target tracking
Published 2025-12-01“…First, a specialized lightweight target detection algorithm, YOLOv8s-Longan, is developed to achieve high-precision target localization and facilitate lightweight model deployment. …”
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6670
Overhead line path planning based on deep reinforcement learning and geographical information system
Published 2025-04-01“…Experimental verification of real data shows that compared with existing algorithms, the DSOP method is not only more consistent with the manual line selection effect (improved by more than 3%), but also has a high success rate. …”
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6671
Predicting Employee Turnover Using Machine Learning Techniques
Published 2025-01-01“…This study aims to identify the most effective machine learning model for predicting employee attrition, thereby providing organizations with a reliable tool to anticipate turnover and implement proactive retention strategies.Objective: This study aims to address the challenge of employee attrition by applying machine learning techniques to provide predictive insights that can improve retention strategies.Methods: Nine machine learning algorithms are applied to a dataset of 1,470 employee records. …”
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6672
Intracardiac abscess in the clinical course of infective endocarditis complicated by acute heart failure
Published 2024-12-01“…Objective: to determine the optimal diagnostic and treatment algorithm for patients with infective endocarditis complicated by acute heart failure (AHF) and intracardiac abscess. …”
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6673
An Adaptive Weight Physics-Informed Neural Network for Vortex-Induced Vibration Problems
Published 2025-05-01“…In this study, a VIV dataset of a cylindrical body with different degrees of freedom is used to compare the performance of the PINN and three PINN optimization algorithms. The findings suggest that, compared to a standard PINN, the AW-PINN lowers the mean squared error (MSE) on the test set by 50%, significantly improving the prediction accuracy. …”
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6674
Intelligent Data Reduction for IoT: A Context-Driven Framework
Published 2025-01-01“…With these predictions based on existing datasets, a selector algorithm module is adopted to identify the most suitable data reduction approach for specific IoT applications. …”
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6675
Research on Urban Traffic Signal Control Systems Based on Cyber Physical Systems
Published 2020-01-01“…Finally, considering China, the system designs a general control strategy API to separate data from control strategy. Most of the popular communication protocols between signal controllers and detectors are private protocols. …”
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6676
DS-AdaptNet: An Efficient Retinal Vessel Segmentation Framework With Adaptive Enhancement and Depthwise Separable Convolutions
Published 2025-01-01“…Second, we develop a Context-Aware Adaptive Threshold Optimization (CA-ATO) algorithm that dynamically determines optimal thresholds by integrating multi-scale contextual information and uncertainty estimates, substantially improving boundary delineation accuracy and fine structure preservation. …”
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6677
Intelligent resource allocation in internet of things using random forest and clustering techniques
Published 2025-08-01“…A Random Forest model is then trained to accurately predict the resource needs of each cluster, enabling optimal allocation. …”
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6678
Performance and emission analysis of CI engine fueled with Dunaliella salina biodiesel and TiO₂ nanoparticle additives: Experimental and ANN-based Predictive Approach
Published 2025-09-01“…An Artificial Neural Network (ANN) model was developed using the Levenberg-Marquardt algorithm, incorporating 27 datasets generated through a Response Surface Methodology (RSM)-based d-optimal design to predict engine performance and emission characteristics. …”
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6679
City-scale industrial tank detection using multi-source spatial data fusion
Published 2024-12-01“…To address this, high-resolution remote sensing images and deep learning algorithms are used to improve the accuracy of industrial storage tank detection at the city scale. …”
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6680
A New Approach to ORB Acceleration Using a Modern Low-Power Microcontroller
Published 2025-06-01“…This work also allows for future optimizations that will improve the results of this paper.…”
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