机译:在压缩传感域下使用交叉连接的卷积神经网络有效的交通标志识别
Zhejiang Normal Univ Coll Phys & Elect Informat Engn Jinhua Zhejiang Peoples R China;
Zhejiang Normal Univ Coll Phys & Elect Informat Engn Jinhua Zhejiang Peoples R China;
Univ Elect Sci & Technol China Sch Aeronaut & Astronaut Chengdu 611731 Peoples R China;
Zhejiang Normal Univ Coll Phys & Elect Informat Engn Jinhua Zhejiang Peoples R China;
Zhejiang Normal Univ Coll Phys & Elect Informat Engn Jinhua Zhejiang Peoples R China;
Zhejiang Normal Univ Coll Phys & Elect Informat Engn Jinhua Zhejiang Peoples R China;
Compressive sensing domain; Convolution neural networks; CS measurements; Simulated traffic sign recognition;
机译:交通标志识别新型遗传优化的卷积神经网络:比利时和中国交通标志数据集的新基准
机译:基于SVM和卷积神经网络的两阶段交通标志检测与识别
机译:推动“限速”:卷积神经网络的高精度美国交通标志识别
机译:使用卷积神经网络识别车辆,行人和交通标志
机译:基于深度卷积神经网络设计交通符号分类有效模型
机译:使用深度卷积神经网络的无预训练的参考驱动压缩感测MR图像重建
机译:使用卷积神经网络的交通标志识别