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,Feature Fusion Expression Recognition Algorithm Based on DCA Dimensionality Reduction,s proposed. The algorithm firstly extracts the expression features of the preprocessed data by using the improved HOG-LBP algorithm, then uses the improved discriminative correlation analysis algorithm to reduce the dimension of the feature information. Experimental results show that the improved al

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,Decision Tree Fusion and Improved Fundus Image Classification Algorithm,mage is divided into three channels of RGB, and the extracted green channel image is enhanced with the Butterworth parameter function of the fusion power function. Then the improved UNet++ network model is used to extract the texture features of the fundus image, and the residual module is used to e

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,Traffic Sign Image Segmentation Algorithm Based on Improved Spatio-Temporal Map Convolution,mporal component graph convolution network for the problem of road traffic sign recognition in a complex environment. The algorithm uses octave convolution to reduce the computational effort to improve the recognition speed and uses a spatio-temporal graph convolution network to recognize traffic si

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,A Blockchain-Based Distributed Machine Learning (BDML) Approach for Resource Allocation in Vehiculaiency, and a high risk of privacy leakage, the use of traditional centralized data centers to analyze massive data has proven to be a difficult task. These challenges have prompted a revolutionary change in VANET architectures to scatter computations from a centralized data center to distributed net

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Deployment Strategy of Highway RSUs for Vehicular Ad Hoc Networks Considering Accident Notificationtical analysis model is established by analyzing the relationship between the delivery delay of accident notification information and the deployment of RSUs in the Vehicular Ad Hoc Networks (VANETs). The model assumes that two adjacent RSUs are connected, and considers the impact of accident probabi

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