How to recognize targets with similar appearances from remote sensing images(RSIs) effectively and efficiently has become a big challenge. Recently, convolutional neural network(CNN) is preferred in the target classif...How to recognize targets with similar appearances from remote sensing images(RSIs) effectively and efficiently has become a big challenge. Recently, convolutional neural network(CNN) is preferred in the target classification due to the powerful feature representation ability and better performance. However,the training and testing of CNN mainly rely on single machine.Single machine has its natural limitation and bottleneck in processing RSIs due to limited hardware resources and huge time consuming. Besides, overfitting is a challenge for the CNN model due to the unbalance between RSIs data and the model structure.When a model is complex or the training data is relatively small,overfitting occurs and leads to a poor predictive performance. To address these problems, a distributed CNN architecture for RSIs target classification is proposed, which dramatically increases the training speed of CNN and system scalability. It improves the storage ability and processing efficiency of RSIs. Furthermore,Bayesian regularization approach is utilized in order to initialize the weights of the CNN extractor, which increases the robustness and flexibility of the CNN model. It helps prevent the overfitting and avoid the local optima caused by limited RSI training images or the inappropriate CNN structure. In addition, considering the efficiency of the Na¨?ve Bayes classifier, a distributed Na¨?ve Bayes classifier is designed to reduce the training cost. Compared with other algorithms, the proposed system and method perform the best and increase the recognition accuracy. The results show that the distributed system framework and the proposed algorithms are suitable for RSIs target classification tasks.展开更多
With the ever-spreading of international globalization and much frequent communication among countries in politics, economics and culture. Interpretation which serves as communicative bridge between different language...With the ever-spreading of international globalization and much frequent communication among countries in politics, economics and culture. Interpretation which serves as communicative bridge between different languages, which has become an important inter-lingual communicative device. In order to meet the demand of the growing need for interpreting talents, more and more institutions of higher learning begin to set up translation and interpretation courses for undergraduate and graduate students. The thesis focuses on making a brief analysis on the present situation of interpreting courses of graduate students in Inner Mongolian Autonomous Region. The thesis is composed of three parts： the first part is a brief analysis of the interpreting features of graduate students in Inner Mongolia, the second part analyzes the principles of interpreting training from the perspective of interpretive theory. The third part is the suggestions for interpreting training so as to make a contribution to the teaching of interpreting in Inner Mongolia.展开更多
Ultimately,the fundamental issues of educational sciences remain economic and societal.The interactions between“business”culture,“professional”culture and training are part of this.This contribution is a reflectio...Ultimately,the fundamental issues of educational sciences remain economic and societal.The interactions between“business”culture,“professional”culture and training are part of this.This contribution is a reflection resulting from a longitudinal empirical research entitled:“Professionalization of an establishment in the social and medico-social field:a French monograph after the law 2002-02 of January 02,2002”.Three concepts were used:“making sense”(Weick,1995);the“strategic paradigm”(Jonhson,1987);and“cultures of action”(Sorel&Wittorski,2005;Barbier,2010;Ardouin,2015).展开更多
基金supported by the National Natural Science Foundation of China(U1435220)
文摘How to recognize targets with similar appearances from remote sensing images(RSIs) effectively and efficiently has become a big challenge. Recently, convolutional neural network(CNN) is preferred in the target classification due to the powerful feature representation ability and better performance. However,the training and testing of CNN mainly rely on single machine.Single machine has its natural limitation and bottleneck in processing RSIs due to limited hardware resources and huge time consuming. Besides, overfitting is a challenge for the CNN model due to the unbalance between RSIs data and the model structure.When a model is complex or the training data is relatively small,overfitting occurs and leads to a poor predictive performance. To address these problems, a distributed CNN architecture for RSIs target classification is proposed, which dramatically increases the training speed of CNN and system scalability. It improves the storage ability and processing efficiency of RSIs. Furthermore,Bayesian regularization approach is utilized in order to initialize the weights of the CNN extractor, which increases the robustness and flexibility of the CNN model. It helps prevent the overfitting and avoid the local optima caused by limited RSI training images or the inappropriate CNN structure. In addition, considering the efficiency of the Na¨?ve Bayes classifier, a distributed Na¨?ve Bayes classifier is designed to reduce the training cost. Compared with other algorithms, the proposed system and method perform the best and increase the recognition accuracy. The results show that the distributed system framework and the proposed algorithms are suitable for RSIs target classification tasks.
文摘With the ever-spreading of international globalization and much frequent communication among countries in politics, economics and culture. Interpretation which serves as communicative bridge between different languages, which has become an important inter-lingual communicative device. In order to meet the demand of the growing need for interpreting talents, more and more institutions of higher learning begin to set up translation and interpretation courses for undergraduate and graduate students. The thesis focuses on making a brief analysis on the present situation of interpreting courses of graduate students in Inner Mongolian Autonomous Region. The thesis is composed of three parts： the first part is a brief analysis of the interpreting features of graduate students in Inner Mongolia, the second part analyzes the principles of interpreting training from the perspective of interpretive theory. The third part is the suggestions for interpreting training so as to make a contribution to the teaching of interpreting in Inner Mongolia.
文摘Ultimately,the fundamental issues of educational sciences remain economic and societal.The interactions between“business”culture,“professional”culture and training are part of this.This contribution is a reflection resulting from a longitudinal empirical research entitled:“Professionalization of an establishment in the social and medico-social field:a French monograph after the law 2002-02 of January 02,2002”.Three concepts were used:“making sense”(Weick,1995);the“strategic paradigm”(Jonhson,1987);and“cultures of action”(Sorel&Wittorski,2005;Barbier,2010;Ardouin,2015).
