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Found 4 papers, 1 papers with code
Improving adversarial robustness of deep neural networks by using semantic information
The vulnerability of deep neural networks (DNNs) to adversarial attack, which is an attack that can mislead state-of-the-art classifiers into making an incorrect classification with high confidence by deliberately perturbing the original inputs, raises concerns about the robustness of DNNs to such attacks.
Spec-ResNet: A General Audio Steganalysis scheme based on Deep Residual Network of Spectrogram
The proposed scheme has better detection accuracy for three different AAC steganographic schemes and MP3Stego than the state-of-arts steganalysis schemes which are based on traditional hand-crafted or CNN-based feature.
Multimedia
A Procedural Texture Generation Framework Based on Semantic Descriptions
Finally, given a set of semantic descriptions, the diverse properties of the samples in the semantic space can lead the framework to find an appropriate generation model that uses appropriate parameters to produce a desired texture.
An Overview on Data Representation Learning: From Traditional Feature Learning to Recent Deep Learning
Since about 100 years ago, to learn the intrinsic structure of data, many representation learning approaches have been proposed, including both linear ones and nonlinear ones, supervised ones and unsupervised ones.
