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Found 6 papers, 0 papers with code
A novel image tag completion method based on convolutional neural network
In this paper, we study the problem of image tag complete and proposed a novel method for this problem based on a popular image representation method, convolutional neural network (CNN).
Learning convolutional neural network to maximize Pos@Top performance measure
The CNN model is used to represent the multi-instance data point, and a classifier function is used to predict the label from the its CNN representation.
Stochastic Learning of Multi-Instance Dictionary for Earth Mover's Distance based Histogram Comparison
These bags are mapped to histograms using a multi-instance dictionary.
A novel transfer learning method based on common space mapping and weighted domain matching
We map the data of two domains to one single common space, and learn a classifier in this common space.
Semi-supervised structured output prediction by local linear regression and sub-gradient descent
The existing semi-supervise structured output prediction methods learn a global predictor for all the data points in a data set, which ignores the differences of local distributions of the data set, and the effects to the structured output prediction.
Optimizing Top Precision Performance Measure of Content-Based Image Retrieval by Learning Similarity Function
To fill this gap, in this paper, we propose a novel similarity learning method to maximize the top precision measure.
