QUANTIFYING THE ALIGNMENT OF GRAPH AND FEATURES IN DEEP LEARNING

 We show that the classification performance of graph convolutional networks (GCNs) is related to the alignment between features, graph, and ground truth, which we quantify using a subspace alignment measure (SAM) corresponding to the Frobenius norm of the matrix of pairwise chordal distances between three subspaces associated with features, graph, ...

DEEP LEARNING FEATURES IN DEEP LEARNING

QUANTIFYING THE ALIGNMENT OF GRAPH AND FEATURES IN DEEP LEARNING

 We show that the classification performance of graph convolutional networks (GCNs) is related to the alignment between features, graph, and ground truth, which we quantify using a subspace alignment measure (SAM) corresponding to the Frobenius norm of the matrix of pairwise chordal distances between three subspaces associated with features, graph, ...

DEEP LEARNING FEATURES

Composite Kernel of Mutual Learning on Mid-Level Features for Hyperspectral Image Classification

 By training different models and averaging their predictions, the performance of the machine-learning algorithm can be improved. The performance optimization of multiple models is supposed to generalize further data well. This requires the knowledge transfer of generalization information between models. In this article, a multiple kernel mutual lea...

Unsupervised Domain Adaptation for Cloud Detection Based on Grouped Features Alignment and Entropy Minimization

 Most convolutional neural network (CNN)-based cloud detection methods are built upon the supervised learning framework that requires a large number of pixel-level labels. However, it is expensive and time-consuming to manually annotate pixelwise labels for massive remote sensing images. To reduce the labeling cost, we propose an unsupervised domain...

NISA Node Identification and Spoofing Attack Detection Based on Clock Features and Radio Information for Wireless Sensor Networks

 Node identification based on unique hardware features like clock skews has been considered an efficient technique in wireless sensors networks (WSNs). Spoofing attacks imitating unique hardware features, however, could significantly impair or break down conventional clock-skew-based node identification due to exposed clock information through broad...

WELFake Word Embedding Over Linguistic Features for Fake News Detection

 Social media is a popular medium for the dissemination of real-time news all over the world. Easy and quick information proliferation is one of the reasons for its popularity. An extensive number of users with different age groups, gender, and societal beliefs are engaged in social media websites. Despite these favorable aspects, a significant disa...

Phishing Web Sites Features Classification Based on Extreme Learning Machine

 Phishing is the act of attempting to acquire information such as usernames, passwords, and credit card details by masquerading as a trust worth entity in an electronic communication there are several different techniques to control phishing, including legislation and technology created specifically to protect against phishing. This project provides...

Phishing Web Sites Features Classification Based on Extreme Learning Machine

  Phishing is the act of attempting to acquire information such as usernames, passwords, and credit card details by masquerading as a trust worth entity in an electronic communication there are several different techniques to control phishing, including legislation and technology created specifically to protect against phishing. This project provide...