Self-Supervised Learning-Based Time Series Classification via Hierarchical Sparse Convolutional Masked-Autoencoder

In recent years, the use of time series analysis has become widespread, prompting researchers to explore methods to improve classification.Time series self-supervised learning has emerged as a significant area of study, aiming to uncover patterns in unlabeled data for richer information.Contrastive self-supervised learning, particularly, has gained

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Adversarial Attacks with Defense Mechanisms on Convolutional Neural Networks and Recurrent Neural Networks for Malware Classification

In the field of behavioral detection, deep learning has been extensively utilized.For example, deep learning models have been utilized to detect and classify malware.Deep learning, however, has vulnerabilities that can be exploited with crafted inputs, resulting in malicious files being misclassified.Cyber-Physical Systems (CPS) may be compromised

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