Sentence examples for based on the cnn from inspiring English sources

In this paper, firstly, we proposed a kind of higher layer visualizing feature extraction algorithm based on the SAE model; then, we used the transfer learning methods to realize the global higher layer feature obtained from the small sample target objects in the sky based on the CNN model.

The platform is based on the Cellular Neural/Nonlinear Network (CNN) paradigm.

In the third instar larvae eye disc, it was reported that Cnn was basally positioned in epithelial neuronal precursors, based on the localization of Cnn-GFP expression [38].

In this paper we propose a passenger counting system based on the convolutional neural network (CNN) and the spatio-temporal context (STC) model, where the CNN model is used to detect the passengers and the STC model is used to track the moving head of each passenger, respectively.

Except [18, 36], which presented classifiers based on the Convolutional Neural Networks (CNN), most of the work cited above was presented as variants of the Support Vector Machine (SVM).

The second subnet is a competitive neural network (CNN) based on the winner takes all algorithm (WTA) that is used for the classification.

Based on the 3D images and evaluation criterion, one localization CNN and five AI CNNs are jointly used to evaluate the AI of each aggregate.

Based on the genetic interaction between baz and cnn in the eyes, we needed to determine the localization of Cnn in developing pupal eyes, where the cell polarity genes' roles were well characterized [2], [3], [6], [7], [11].

1in-GEINet vs. Siamese, MT, and LB In 1in-GEINet, namely, the method based on CNN with one input, the parameters of CNN are trained so that the soft-max of the node of fc4 layer corresponding to the same subject as input GEI can be high.

The recognition CNN was designed to distinguish concealed cracks from other types of damage in a GPR image, the location CNN determined the location and length measurement of concealed crack images based on the results provided by the recognition CNN, and crack feature points were extracted by the feature extraction CNN to establish the 3D reconstruction models of the concealed cracks.

Our results strongly suggest that Cnn specifically controls membrane domain size of the apical domain and AJs during pupal eye development based on the genetic interaction (Figure 2), loss-of-function (Figure 4) and gain-of-function (Figure 5) phenotypes of cnn.