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Titlebook: Embedded Systems Technology; 15th National Confer Yuanguo Bi,Gang Chen,Yi Wang Conference proceedings 2018 Springer Nature Singapore Pte Lt

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G. M. Djordjevic,T. R. Klaenhammeral models are built to analyze the EV usage behavior in the urban area. The features such as charging demand, high energy consumption area, and highly traveled paths are captured. We evaluate the proposed models on a real-world EV dataset. The results clearly demonstrate the efficiency and accuracy of our models on locating EV charging stations.
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Pedestrian Detection with D-CNNot in daily life. Among the state-of-the-art methods compared in this paper, the comprehensive performance of D-CNN is the best, whose mAP is only 0.4 points lower than the highest one but the detection speed doubles. So our proposed network can get real-time speed while maintaining rather satisfying precision of pedestrian detection.
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Methods for Partial Differential Equationsocessing, and then make classification of them, so as to realize the recognition of traffic signs. The correct rate of the algorithm which is used in this paper is 98.13%, by processing the experiment on the GTSRB data set.
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