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An improved faster region-based convolutional neural network (R-CNN) [same object retrieval (SOR) faster R-CNN] is proposed to retrieve the same object in different scenes with few training samples. By concatenating the feature maps of shallow and deep convolutional layers, the ability of Regions of Interest (RoI) pooling to extract more detailed features is improved. In the training process, a pretrained...
In this paper, an ontology-based framework of China Geographic National Conditions Monitoring (CGNCM) land cover extraction is presented. Using statistical analysis method, spectral, texture, spatial features of each land cover class are extracted from the referenced ZY-3 image acquired in summer, 2012. Stored in the form of OWL, the features of one class can be considered as the prototype of this...
After analyzing flexibility material processing (such as quilting processing) influencing factor of pattern deformation, the edges of the original image and the deformation image are extracted. Then they are changed into coordinate. On top of it, the data are put into the Elman neural networks to train which has been built and the original image is used to as the teacher signal to tutoring. At last,...
Rigid registration of intraoperative ultrasound (US) and CT is an important technique to provide real-time guidance for preoperative images and models. Due to the speckle noise and artefacts in US images, accurate registration of CT and US is still a challenging problem. We propose an adaptive region intensity based CT and US registration method. The registration is initialized by matching the distinctive...
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