Fujitsu Corporation

Mengjiao Wang

Rujie Liu

There are provided a method of knowledge transferring, an information processing apparatus and a storage medium. The method of knowledge transferring includes: obtaining a first model which has been trained in advance with respect to a predetermined task; and training a second model with respect to the predetermined task by utilizing a comprehensive loss function, such that the second model has knowledge of the first model. The comprehensive loss function is based on a first loss function weighted by accuracy of an output result of the first model for a training sample in regard to the predetermined task, and a second loss function. The first loss function represents a difference between processing results of the second model and the first model for the training sample. The second loss function represents accuracy of an output result of the second model for the training sample in regard to the predetermined task.

Method of knowledge transferring, information processing apparatus and storage medium

An information processing method and an information processing apparatus are disclosed, where the information processing method includes: inputting a plurality of samples to a classifier respectively, to extract a feature vector representing a feature of each sample; and updating parameters of the classifier by minimizing a loss function for the plurality of samples, wherein the loss function is in positive correlation with an intra-class distance for representing a distance between feature vectors of samples belonging to a same class, and is in negative correlation with an inter-class distance for representing a distance between feature vectors of samples belonging to different classes, wherein the intra-class distance of each sample of the plurality of samples is less than a first threshold, the inter-class distance between two different classes is greater than a second threshold, and the second threshold is greater than twice the first threshold.

Information processing method and information processing apparatus for improving the discriminality of features of extracted samples

The present application relates to method and device for determining image similarity that includes: dividing a target image into multiple regions based on positions of pixels relative to a reference point in the target image, and dividing a reference image into multiple regions based on positions of pixels relative to a reference point in the reference image; determining, based on feature points in the target image and feature points in the reference image as well as the regions obtained by dividing the target image and the regions obtained by dividing the reference image, similarity between a distribution of the feature points in the target image and a distribution of the feature points in the reference image. According to the method of the present application, the similarity is described more reasonably.

Method and device for determining image similarity

An image processing device and an image processing method are provided. The image processing device includes: an acquisitor configured to acquire multiple slice images arranged in an order; a selector configured to detect the multiple slice images sequentially, to determine a reference slice image and a reference trachea region in the reference slice image; and a branch point determiner configured to determine, with a region growing method, trachea regions of slice images following the reference slice image sequentially by using the reference trachea region as a seed region, and determine connectivity of the trachea regions, until a branch point slice image is determined, where a trachea region of the branch point slice image includes two disconnected regions. With the image processing device and the image processing method, manual intervention can be reduced and a position of the branch point can be determined more accurately.

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Beijing, China

Mengjiao Wang