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AE-FPN: adaptive enhance feature learning for detecting wire defects
Wire defects usually occur in high-altitude transmission lines, leading to line transmission failures and even the possibility of large-scale power...
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D-AE: A Discriminant Encode-Decode Nets for Data Generation
Imbalanced datasets often result in poor predictive model performance. To address this, minority class sample expansion is used, but two challenges...
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AE-TPGG: a novel autoencoder-based approach for single-cell RNA-seq data imputation and dimensionality reduction
Single-cell RNA sequencing (scRNA-seq) technology has become an effective tool for high-throughout transcriptomic study, which circumvents the...
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AE-Reorient: Active Exploration Based Reorientation for Robotic Pick-and-Place
Finding objects in dense clutter and placing them in specific poses play an important role in robot manipulation in fields like warehousing and...
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Industrial Time-Series Signal Anomaly Detection Based on G-LSTM-AE Model
In practical industrial scenarios, efficient anomaly detection is important for the development of industrial system safety and maintenance. In this...
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Data Balancing Technique Based on AE-Flow Model for Network Instrusion Detection
In network intrusion detection, the frequency of some rare network attacks is low, and such samples collected are relatively few. It results in an...
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OF-AE: Oblique Forest AutoEncoders
We propose an unsupervised ensemble method consisting of oblique trees that can address the task of auto-encoding, which is an extension of the...
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Differential fault attack on SPN-based sponge and SIV-like
AE schemesThis paper presents the first instance of a successful differential fault attack (
DFA ) on the nonce-based authentication scheme PHOTON-BEETLE , which...
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Intrusion Detection Model Based on KNN-AE-DNN
As an important aspect of industrial control security information, the field of intrusion detection has been plagued by the problems of high false...
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Modeling and Simulation Based on Concurrent FC-AE-1553 Network
In order to meet the demand of avionics system for high reliability, high determinacy and high bandwidth utilization of airborne network, this paper...
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Reconstructing Electricity Profiles in Submetering Systems Using a GRU-AE Network
Data are key for providing added value in the Industry 4.0 paradigm, benefiting differentiation and innovation. However, high quality data, i.e.,...
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PCA-AE: Principal Component Analysis Autoencoder for Organising the Latent Space of Generative Networks
Autoencoders and generative models produce some of the most spectacular deep learning results to date. However, understanding and controlling the...
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Parallel Verification of Serial MAC and AE Modes
A large number of the symmetric-key mode of operations, such as classical CBC-MAC, have serial structures. While a serial mode gives an...
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PAE: Towards More Efficient and BBB-Secure AE from a Single Public Permutation
Four observations can be made regarding recent trends that have emerged in the evolution of authenticated encryption schemes: (1) regarding...
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AE-LSTM Based Anomaly Detection System for Communication Over DNP 3.0
Energy Management System (EMS) communicates with power plants and substations to maintain the reliability and efficiency of power supplies. EMS...
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Power System Transient Stability Prediction in the Face of Cyber Attacks: Employing LSTM-AE to Combat Falsified PMU Data
Phasor measurement units (PMUs) are essential instruments in delivering real-time data crucial for monitoring the dynamics of power systems. They are...
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Autoencoders (AE)
So far, we have presented various deep learning models for supervised learning where output labels (e.g., heart failure diagnosis) are available in...
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AE-LSTM: A Hybrid Approach for Detecting Deepfake Videos in Digital Forensics
Deepfakes can have serious implications for security, privacy, and trust, as deepfake can be utilized for the purpose of spreading misinformation,...
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An Extreme Learning Machine-Based AutoEncoder (ELM-AE) for Denoising Knee X-ray Images and Grading Knee Osteoarthritis Severity
Osteoarthritis (OA) is the most usual form of arthritis. Radiologists assess the OA severity by observing the pieces of evidence on both sides of...
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AE-CNN Based Supervised Image Classification
Point of Care Ultrasound (PoCUS) imaging is an important tool in detecting lung consolidations and tissue sliding, and hence has a potential to...