This work presents an approach on high-level semantic feature detection in video sequences. Keyframes are selected to represent the visual content of the shots. Then, low-level feature extraction is performed on the keyframes and a feature vector including color and texture features is formed. A region thesaurus that contains all the high-level features is constructed using a subtractive cluste...

To study the generation of the semantic tree of Chinese sentence in Chinese-English Machine translation (MT), a new semantic-analysis model of Chinese multiplebranched and multiple-labeled tree (MMT) based on the hierarchical network of concepts (HNC) is proposed. Supported by word and rule knowledge-base of HNC, the model executed the semantic analysis using static and dynamic labels as a comp...

Problem statement: Text documents are the unstructured databases that contain raw data collection. The clustering techniques are used group up the text documents with reference to its similarity. Approach: The feature selection techniques were used to improve the efficiency and accuracy of clustering process. The feature selection was done by eliminate the redundant and irrelevant items from th...

Machine learning models have demonstrated vulnerability to adversarial attacks, more specifically misclassification of examples. In this article, we propose a one-off and attack-agnostic Feature Manipulation (FM)-Defense detect purify examples in an interpretable efficient manner. The intuition is that the classification result normal image generally resistant non-significant intrinsic feature ...

We propose spectral analysis to investigate the correlation between accuracy and resolution of segmentation maps for semantic segmentation. The current networks predict on down-sampled grid images alleviate computational cost. Moreover, these can be trained by weak annotations that utilize only coarse contour maps. Despite successful achievement works utilizing low-frequency information maps, h...

Deep neural networks have been shown to be vulnerable adversarial attacks that perturb inputs based on semantic features. Existing robustness analyzers can reason about feature neighborhoods increase the networks’ reliability. However, despite significant progress in these techniques, they still struggle scale deep and large neighborhoods. In this work, we introduce VeeP, an active learning app...