Search Results - Memory-based additional autoencoder

Unsupervised Unknown Radar Waveform Detection by Yoon, Jaehyeok, Nam, Haewoon

“… The proposed method integrates a Deep Shrinkage Autoencoder (DSAE) and a Memory-Augmented Additional Autoencoder (MAAE…”
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Advanced memory forensics for malware classification with deep learning algorithms by Odeh, Ammar, Taleb, Anas Abu, Alhajahjeh, Tareq, Navarro, Francisco

“… Memory-based features, including memory pages, threads, open files, user sessions, system calls, and kernel modules, were extracted from memory dumps using the Volatility and Rekall frameworks…”
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A Secure, Blockchain-Enabled Vehicular Sensor Communication Protocol With Deep Learning-Assisted Anomaly Detection by Mishra, Sumit, Sengar, Neha, Har, Dongsoo

“… The experimental results show that the proposed long short-term memory-based model is effective in detecting anomalies…”
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Machine Learning Based Flip-Flop Grouping for Toggling Driven Clock Gating by Park, Sora, Kim, Taewhan

“… Precisely, we develop a neural network model of LSTM (long short-term memory) based AE (autoencoder) model combined with SDAE…”
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DROPSYS: Detection of ROP attacks using system information by Kim, Seon Kwon, Jin, Hongjoo, Joo, Kyungho, Lee, Jiwon, Lee, Dong Hoon

“…) to mitigate concerns about additional cost and compatibility issues. However the existing HPC data-based ROP detection techniques typically suffer from low detection performance mainly because of the non-deterministic nature of HPCs…”
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Anomaly Detection Reliability in Consumer Electronics Manufacturing by Pai, Chuen-Wun, Hsueh, Hung-Wei, Hsu, Shu-han

“… To address these gaps, this study provides an in-depth analysis of the reliability of autoencoders, a representative anomaly detection model, at various levels of granularity…”
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基于块金字塔记忆模块的无监督异常检测 by 鄢宁, 李岳阳, 罗海驰

“…TP391.41; 基于重建的无监督异常检测方法由于不需要异常样本和预训练模型,被广泛地应用到异常检测任务中.然而,在实际应用中由于卷积神经网络的泛化性,模型能够有效地重建…”
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Dynamic Local Aggregation Network with Adaptive Clusterer for Anomaly Detection by Yang, Zhiwei, Wu, Peng, Liu, Jing, Liu, Xiaotao

“…Existing methods for anomaly detection based on memory-augmented autoencoder (AE) have the following drawbacks…”
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