In this paper, we introduced the higher layer visualizing feature extraction method based on the hybrid deep network model to obtain the higher layer feature through combining the Sparse Autoencoder (SAE) model, the Convolutional Neural Network (CNN) model, and the regression classifier model to classify the different types of the target object images.
Finally, the global feature can be sent into the classifier (such as logistic or Softmax regression model) to classify the small sample target objects in the test set.
The leave-one-out cross validation technique is closer to the personalized modelling approach, when for every new individual data sample, we create a model to classify (predict) the outcome of this individual, using all available data samples of other individuals, and derive a personalized profile of the individual [ 21].
In [4], Ma and Grimson modified this constellation model to classify vehicles in two-class problem.
As a result, they proposed a new model to classify wastes in IT organizations.
Apple then applies a machine learning model to classify which top privately controlled domains have the ability to track the user cross-site, based on the collected statistics.
By processing these segments only, we may further employ such method as hidden Markov model to classify their content.
Inferred uses a latent class model to classify respondents depending on the estimated probability that respondents ignore selected attributes.
Data sets thus generated were used to build a feed-forward neural network (NN) model to classify the vapors.
In the second step, the system applies a personalized model to classify a user in one of the three categories (e.g., legitimate, naive adversary, and strong adversary).
In [37], the authors use a factor analysis approach to adapt a universal GMM model to classify BN in five different classes.
