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Hepatic CT Image Query Based on Threshold-based Classification Scheme with Gabor Features
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作者 蒋历军 罗永兴 +1 位作者 赵俊 庄天戈 《Journal of Shanghai Jiaotong university(Science)》 EI 2008年第6期753-758,共6页
Hepatic computed tomography(CT) images with Gabor function were analyzed.Then a threshold-based classification scheme was proposed using Gabor features and proceeded with the retrieval of the hepatic CT images.In our ... Hepatic computed tomography(CT) images with Gabor function were analyzed.Then a threshold-based classification scheme was proposed using Gabor features and proceeded with the retrieval of the hepatic CT images.In our experiments, a batch of hepatic CT images containing several types of CT findings was used and compared with the Zhao's image classification scheme, support vector machines(SVM) scheme and threshold-based scheme. 展开更多
关键词 content based image retrieval Gabor features threshold-based scheme support vector machines (SVM) hepatic computed tomography (CT) images
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A new detector in EBPSK communication system
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作者 靳一 吴乐南 +1 位作者 王继武 余静 《Journal of Southeast University(English Edition)》 EI CAS 2011年第3期244-247,共4页
In order to raise the detection precision of the extended binary phase shift keying (EBPSK) receiver, a detector based on the improved particle swarm optimization algorithm (IMPSO) and the BP neural network is des... In order to raise the detection precision of the extended binary phase shift keying (EBPSK) receiver, a detector based on the improved particle swarm optimization algorithm (IMPSO) and the BP neural network is designed. First, the characteristics of EBPSK modulated signals and the special filtering mechanism of the impacting filter are demonstrated. Secondly, an improved particle swarm optimization algorithm based on the logistic chaos disturbance operator and the Cauchy mutation operator is proposed, and the EBPSK detector is designed by utilizing the IMPSO-BP neural network. Finally, the simulation of the EBPSK detector based on the MPSO-BP neural network is conducted and the result is compared with that of the adaptive threshold-based decision, the BP neural network, and the PSO-BP detector, respectively. Simulation results show that the detection performance of the EBPSK detector based on the IMPSO-BP neural network is better than those of the other three detectors. 展开更多
关键词 extended binary phase shift keying DETECTOR impacting filter logistic chaos disturbance Cauchy mutation adaptive threshold-based decision
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