Titlebook: Intelligent Computing Theories and Application; 15th International C De-Shuang Huang,Vitoantonio Bevilacqua,Prashan Pre Conference proceedi

幼稚

埋葬

considerable

Ligament

A Deep Learning Model for Multi-label Classification Using Capsule Networks,s is much larger than the number of single-labeled images, which means that the study of multi-label image classification is more important. Most of the published network for multi-label image classification uses a CNN with a sigmoid layer, which is different from the single-label classification net

情感脆弱

BATE

Combining LSTM Network Model and Wavelet Transform for Predicting Self-interacting Proteins,tention to the development of approaches for the prediction of protein interactions and functions from sequences. In addition, elucidation of the self-interacting proteins (SIPs) play significant roles in the understanding of cellular process and cell functions. This work explored the use of deep le

AMOR

Coarse-to-Fine Supervised Descent Method for Face Alignment,res a large amount of training samples to learn the descent directions and get the corresponding regressors. Then in the test phase, it uses the corresponding regressors to estimate the descent directions and locate the facial landmarks. However, when the facial expression or direction changes too m

止痛藥

Prediction of Chemical Oxygen Demand in Sewage Based on Support Vector Machine and Neural Network,d model based on support vector machine and neural network is proposed to predict effluent COD. It can reduce the influence of local optimum on the global scope so as to improve the accuracy of prediction. Firstly, the sample data are divided into two categories by support vector machine. Then the B

殺蟲劑

Relaxed 2-D Principal Component Analysis by Lp Norm for Face Recognition,, the R2DPCA utilizes the label information (if known) of training samples to calculate a relaxation vector and presents a weight to each subset of training data. A new relaxed scatter matrix is defined and the computed projection axes are able to increase the accuracy of face recognition. The optim

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