Zhejiang University

Beijing Didi Infinity Technology and Development Co., Ltd.

Zhaohui Wu

Jianwei Yin

Shuiguang Deng

Ying Li

Jian Wu

Zhiling Luo

Qiang Li

Li Chen

Hui Meng

Gang Pan

Yingchun Yang

Zhiheng Wang

Yueming Wang

Shudong Wang

Dong Xing

Tianming Zhang

Wenqiu Zeng

Yaoyao Hao

Xiaoxiang Zheng

Cunle Qian

Taolue Xue

Guiting Dai

Tianyu Chen

Duoqing Zhou

Yiwen Wang

Yishan Chen

Qiaosheng Zhang

The present disclosure provides methods and systems for vehicle verification. The method may include receiving vehicle verification information related to a vehicle to be verified from a client, wherein the vehicle verification information includes a plurality of images acquired by the client via an imaging device, and the vehicle verification information responds to at least one vehicle verification instruction. The method may further include determining a verification result of the vehicle based on the vehicle verification information.

Methods and systems for vehicle verification

Disclosed in the present invention is a spontaneous edge application deployment and pricing method based on an incentive mechanism. The method comprises the following steps: building an edge end application oriented spontaneous deployment system architecture; then proposing an incentive mechanism aiming at spontaneous edge application deployment and prizing; solving the spontaneous edge application deployment and prizing problem based on a backward induction method, thereby obtaining an optimal deployment solution of an edge server and an optimal prizing strategy of an application provider.

Spontaneous edge application deployment and pricing method based on incentive mechanism

A method and system of graph feature extraction and graph classification based on adjacency matrix is provided. The invention first concentrates the connection information elements in the adjacency matrix into a specific diagonal region of the adjacency matrix which reduces the non-connection information elements in advance. Then the subgraph structure of the graph is further extracted along the diagonal direction using the filter matrix. Further, it uses a stacked convolutional neural network to extract a larger subgraph structure. On one hand, it greatly reduces the amount of computation and complexity, getting rid of the limitations caused by computational complexity and window size. On the other hand, it can capture large subgraph structure through a small window, as well as deep features from the implicit correlation structures at both vertex and edge level, which improves speed and accuracy of graph classification.

System and method of graph feature extraction based on adjacency matrix

Disclosed is system and method of connection information regularization, graph feature extraction and graph classification based on adjacency matrix. By concentrating the connection information elements in the adjacency matrix into a specific diagonal region of the adjacency matrix in order to reduce the non-connection information elements in advance. The subgraph structure of the graph is further extracted along the diagonal direction using the filter matrix. Then a stacked convolutional neural network is used to extract a larger subgraph structure. On the one hand, it greatly reduces the amount of computation and complexity, solving the limitations of the computational complexity and the limitations of window size. And on the other hand, it can capture large subgraph structure through a small window, as well as deep features from the implicit correlation structures at both vertex and edge level, which improves the accuracy and speed of the graph classification.

System and method of connection information regularization, graph feature extraction and graph classification based on adjacency matrix

The present invention is related to a method for prediction of cortical spiking neural signal, comprising the following steps: 1) pretreatment of spiking neural signal, 2) modeling of posterior cortical spiking neural signal generation probability, 3) model accuracy measurement, 4) model optimization with the help of numerical gradient descent and 5) prediction of posterior cortical spiking neural signal with iterative calculation. The prediction method aims to incorporate natural features of point process of spiking neural signal into the target for optimization of prediction model to improve model's capability in predicting neural spike trains.

Method for prediction of cortical spiking trains

A speaker recognition method through emotional model synthesis based on Neighbors Preserving Principle is enclosed. The methods includes the following steps: (1) training the reference speaker's and user's speech models; (2) extracting the neutral-to-emotion transformation/mapping sets of GMM reference models; (3) extracting the emotion reference Gaussian components mapped by or corresponding to several Gaussian neutral reference Gaussian components close to the user's neutral training Gaussian component; (4) synthesizing the user's emotion training Gaussian component and then synthesizing the user's emotion training model; (5) synthesizing all user's GMM training models; (6) inputting test speech and conducting the identification. This invention extracts several reference speeches similar to the neutral training speech of a user from a speech library by employing neighbor preserving principles based on KL divergence and combines an emotion training speech of the user using the emotion reference speech in the reference speech, improving the performance of the speaker recognition system in the situation where the training speech and the test speech are mismatched, and the robustness of the speaker recognition system is increased.

Speaker recognition method through emotional model synthesis based on neighbors preserving principle

A method for semantic service registration and query based on WordNet is disclosed. The method includes the following steps: (1) semantic service registration: a service provider registers a service and uploads the Web Service Description Language (WSDL) document corresponding to the service, and a system parses the WSDL document to form a service description tree, then constructs a WordNet ontology tree according to the input of the service, performs a semantic annotation on the input/output of the service to form a Web Service Semantic Description Document (WSDL-S), and finally stores it in a register library; (2) semantic service discovery: a service requester inputs the information of service type, semantic information of the service input/output and other user-defined information to the register library to retrieve the services meeting the requirements; and (3) similarity sorting: the services meeting a certain threshold are sorted in descending order. The method has the advantages of the combination of WordNet ontology library and the semantic description language of WSDL-S, and definite semantic meaning.

Method for semantic service registration and query based on WordNet

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Hangzhou, China

Zhaohui Wu