基于深度学习的人脸识别技术以数据为驱动,对输入图像的质量要求较高。在铁路刷脸进/出站场景下,为滤除因各种因素导致的成像异常的人脸图像,提升人脸识别精度,文章研究人脸图像正常的特征分布,通过知识迁移,提出无须针对异常样本建模...基于深度学习的人脸识别技术以数据为驱动,对输入图像的质量要求较高。在铁路刷脸进/出站场景下,为滤除因各种因素导致的成像异常的人脸图像,提升人脸识别精度,文章研究人脸图像正常的特征分布,通过知识迁移,提出无须针对异常样本建模的人脸图像异常检测算法。理想情况下,该算法对人脸图像异常检测的ROC曲线下面积(AUROC,Aera Under Receiver Operating Characteristic)可达到0.979。实验结果表明,该算法在计算精度与运行成本的组合上具有较高的自由度,可实现不同场景、硬件条件下的算法适配,为优化旅客人脸识别的输入环节,提高各场景下的旅客人脸识别率提供了技术支撑。展开更多
To preserve the original signal as much as possible and filter random noises as many as possible in image processing,a threshold optimization-based adaptive template filtering algorithm was proposed.Unlike conventiona...To preserve the original signal as much as possible and filter random noises as many as possible in image processing,a threshold optimization-based adaptive template filtering algorithm was proposed.Unlike conventional filters whose template shapes and coefficients were fixed,multi-templates were defined and the right template for each pixel could be matched adaptively based on local image characteristics in the proposed method.The superiority of this method was verified by former results concerning the matching experiment of actual image with the comparison of conventional filtering methods.The adaptive search ability of immune genetic algorithm with the elitist selection and elitist crossover(IGAE) was used to optimize threshold t of the transformation function,and then combined with wavelet transformation to estimate noise variance.Multi-experiments were performed to test the validity of IGAE.The results show that the filtered result of t obtained by IGAE is superior to that of t obtained by other methods,IGAE has a faster convergence speed and a higher computational efficiency compared with the canonical genetic algorithm with the elitism and the immune algorithm with the information entropy and elitism by multi-experiments.展开更多
In order to improve the transmission accuracy and efficiency of sensing and actuating signals in Internet of Things （loT） and ensure the system stability, an adaptive resource allocation algorithm is proposed, which...In order to improve the transmission accuracy and efficiency of sensing and actuating signals in Internet of Things （loT） and ensure the system stability, an adaptive resource allocation algorithm is proposed, which dynami- cally assigns the network bandwidth and priority among components according to their signals＇ frequency domain characteristics. A remote sensed and controlled unmanned ground vehicle （UGV） path tracking test-bed was devel- oped and multiple UGV＇s tracking error signals were measured in the simulation for performance evaluation. Results show that with the same network bandwidth constraints, the proposed algorithm can reduce,, the accumulated and maximum errors of UGV path tracking by over 60% compared with the conventional static algorithm.展开更多
An adaptive technique adopting quantum genetic algorithm （QGA） for antenna impedance tuning is presented. Three examples are given with different types of antenna impedance. The frequency range of the dual standards...An adaptive technique adopting quantum genetic algorithm （QGA） for antenna impedance tuning is presented. Three examples are given with different types of antenna impedance. The frequency range of the dual standards is from 1.7 to 2.2 GHz. Simulation results show that the proposed tuning technique can achieve good accuracy of impedance matching and load power. The reflection coefficient and VSWR obtained are also very close to their ideal values. Comparison of the proposed QGA tuning method with conventional genetic algorithm based tuning method is Moreover, the proposed method can be useful for software wireless bands. also given, which shows that the QGA tuning algorithm is much faster. defined radio systems using a single antenna for multiple mobile and展开更多
n this paper an adaptive robust algorithm for pole-placement design is proposed. It consists of the refined--optimal IV parameter estimator and a robust pole--placement controller. The robustness of the algorithm mean...n this paper an adaptive robust algorithm for pole-placement design is proposed. It consists of the refined--optimal IV parameter estimator and a robust pole--placement controller. The robustness of the algorithm means that the output of the controlled plant can be stabilized in the presence of unmodelled dynamics and bounded unmeasurable output noise. Simulation results show the effeciency of the algorithm.展开更多
文摘基于深度学习的人脸识别技术以数据为驱动,对输入图像的质量要求较高。在铁路刷脸进/出站场景下,为滤除因各种因素导致的成像异常的人脸图像,提升人脸识别精度,文章研究人脸图像正常的特征分布,通过知识迁移,提出无须针对异常样本建模的人脸图像异常检测算法。理想情况下,该算法对人脸图像异常检测的ROC曲线下面积(AUROC,Aera Under Receiver Operating Characteristic)可达到0.979。实验结果表明,该算法在计算精度与运行成本的组合上具有较高的自由度,可实现不同场景、硬件条件下的算法适配,为优化旅客人脸识别的输入环节,提高各场景下的旅客人脸识别率提供了技术支撑。
基金Project(20040533035) supported by the National Research Foundation for the Doctoral Program of Higher Education of ChinaProject (60874070) supported by the National Natural Science Foundation of China
文摘To preserve the original signal as much as possible and filter random noises as many as possible in image processing,a threshold optimization-based adaptive template filtering algorithm was proposed.Unlike conventional filters whose template shapes and coefficients were fixed,multi-templates were defined and the right template for each pixel could be matched adaptively based on local image characteristics in the proposed method.The superiority of this method was verified by former results concerning the matching experiment of actual image with the comparison of conventional filtering methods.The adaptive search ability of immune genetic algorithm with the elitist selection and elitist crossover(IGAE) was used to optimize threshold t of the transformation function,and then combined with wavelet transformation to estimate noise variance.Multi-experiments were performed to test the validity of IGAE.The results show that the filtered result of t obtained by IGAE is superior to that of t obtained by other methods,IGAE has a faster convergence speed and a higher computational efficiency compared with the canonical genetic algorithm with the elitism and the immune algorithm with the information entropy and elitism by multi-experiments.
基金Supported by Natural Science Foundation of Tianjin (No. 07JCZDJC05800)Science and Technology Supporting Plan of Tianjin (No. 09ZCKFGX29200)
文摘In order to improve the transmission accuracy and efficiency of sensing and actuating signals in Internet of Things （loT） and ensure the system stability, an adaptive resource allocation algorithm is proposed, which dynami- cally assigns the network bandwidth and priority among components according to their signals＇ frequency domain characteristics. A remote sensed and controlled unmanned ground vehicle （UGV） path tracking test-bed was devel- oped and multiple UGV＇s tracking error signals were measured in the simulation for performance evaluation. Results show that with the same network bandwidth constraints, the proposed algorithm can reduce,, the accumulated and maximum errors of UGV path tracking by over 60% compared with the conventional static algorithm.
基金Projects(61102039, 51107034) supported by the National Natural Science Foundation of ChinaProject(2011FJ3080) supported by the Planned Science and Technology Project of Hunan Province ChinaProject supported by Fundamental Research Funds for the Central Universities, China
文摘An adaptive technique adopting quantum genetic algorithm （QGA） for antenna impedance tuning is presented. Three examples are given with different types of antenna impedance. The frequency range of the dual standards is from 1.7 to 2.2 GHz. Simulation results show that the proposed tuning technique can achieve good accuracy of impedance matching and load power. The reflection coefficient and VSWR obtained are also very close to their ideal values. Comparison of the proposed QGA tuning method with conventional genetic algorithm based tuning method is Moreover, the proposed method can be useful for software wireless bands. also given, which shows that the QGA tuning algorithm is much faster. defined radio systems using a single antenna for multiple mobile and
文摘n this paper an adaptive robust algorithm for pole-placement design is proposed. It consists of the refined--optimal IV parameter estimator and a robust pole--placement controller. The robustness of the algorithm means that the output of the controlled plant can be stabilized in the presence of unmodelled dynamics and bounded unmeasurable output noise. Simulation results show the effeciency of the algorithm.
