… A predictive spatial model which works well for areas where vegetation is sparse, perhaps
… both in the pattern of response and in the correlation structure, that one finds in spatial data. …

The concept of STREMIS visualization has been proven through user studies using methods
of photo elicitation, participatory observation, and interview with Taiwanese families at …

… He notes that since violent acts have already spread to other regions of China, “[t]herefore
we propose that Xinjiang [has entered] a … painful period of interventionary treatment.” After Xi…

… Neural network-based methods are those that use an artificial neural network (ANN) to learn
classification parameters (using test MR data sets), this learned classification is then used …

… in relevant to pleural effusion and its metastatic contexts. The … Convolutional neural
network(CNN) based deep learning … ) and channel and spatial attention convolutional block …

… Deep learning algorithms such as neural networks and complex combined … brain structure
and physiology as well as patient motor and cognitive symptoms and responses to treatment. …

… individually without the spatial information between them. Also, … To resolve these problems,we
develop a spatial correlation-… through deep learning feature fusion and recurrent neural …

… Early detection of metastasis is important to the treatment, … a deep learning technique to
noninvasively predict genotype in grade II-IV glioma using conventional MR imaging using a …

… spatial distribution of geological bodies, especially for deep … proposed for potential field
edge detection, which is inspired … of deep learning and the advantages of supervised learning. …

… algorithm based on deep learning and transfer learning is proposed. The algorithm is
based on the deep neural network DenseNet structure, and constructs the network model by …