MULTI-LABEL CLASSIFICATION OF STREAMING MEDIA IMAGES BASED ON DEEP LEARNING FRAMEWORK
Considering the problem of multi-label classification of large-scale streaming images with unknown classes,a multi-label classification method based on a deep learning framework is proposed.To detect whether an image contains a new class of labels or not,a recursive class detector was proposed,which learned by efficiently encoding the relationship between image features and multiple labels.To enhance the method's ability to handle large-scale datasets,a batch mode of learning the classifier and detector alternately was effectively implemented by assuming that the new class media images were far away from the known classes in the feature space.The experimental results verify the effectiveness of the method for multi-label classification of large-scale unknown class streaming media images.
Convolution neural networkMulti-LabelStreaming media imageDetector
国家科技期刊平台
NSTL
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