Results 51 to 60 of about 234,412 (208)
Hyperspectral anomaly detection via memory‐augmented autoencoders
CAAI Transactions on Intelligence Technology, 2023 Recently, the autoencoder (AE) based method plays a critical role in the hyperspectral anomaly detection domain. However, due to the strong generalised capacity of AE, the abnormal samples are usually reconstructed well along with the normal background ...
Zhe Zhao, Bangyong Sun
doaj +1 more source
Solving Data Overlapping Problem Using A Class‐Separable Extreme Learning Machine Auto‐Encoder
Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.The overlapping and imbalanced data in classification present key challenges. Class‐separable extreme learning machine auto‐encoding (CS‐ELM‐AE) is proposed, which is an enhancement of ELM‐AE that better handles overlapping data by clustering points from the same class together. Applying oversampling addresses imbalanced data.
Ekkarat Boonchieng, Wanchaloem Nadda
wiley +1 more source
, 2021 This repo includes the datasets that are used to benchmark the experiment results of paper titled "CODE-AE: A Coherent De-confounding Autoencoder for Predicting Patient-Specific Drug Response From Cell Line ...
Di He
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Advanced Intelligent Systems, EarlyView.This paper introduces a resource‐aware Contrastive Scattering Meta‐Learning (CSML) framework for acoustic anomaly detection. By leveraging training‐free wavelet scattering and metric‐based meta‐learning, the model achieves competitive performance with only 50 K learnable parameters—a 98% reduction compared to state‐of‐the‐art frameworks—enabling ...
Rami Zewail, Bassem Mokhtar
wiley +1 more source
, 2023 Recently, anomaly detection in dynamic networks has received increased attention due to massive network-structured data arising in many fields, such as network security, intelligent transportation systems, and computational biology.
Zhen Zhang +4 more
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Health Prognostics Classification with Autoencoders for Predictive Maintenance of HVAC Systems
Energies, 2023 Buildings’ heating, ventilation, and air-conditioning (HVAC) systems account for significant global energy use. Proper maintenance can minimize their environmental footprint and enhance the quality of the indoor environment.
Ruiqi Tian +2 more
doaj +1 more source
A tutorial on multi-view autoencoders using the multi-view-AE library
CoRRThere has been a growing interest in recent years in modelling multiple modalities (or views) of data to for example, understand the relationship between modalities or to generate missing data. Multi-view autoencoders have gained significant traction for their adaptability and versatility in modelling multi-modal data, demonstrating an ability to ...
Ana Lawry Aguila, André Altmann
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Advanced Intelligent Systems, EarlyView.This study introduces a subthreshold in‐memory anomaly detection architecture for wearable ECG monitoring using floating‐gate IGZO content‐addressable memories on a flexible substrate. Area‐engineered coupling provides a high subthreshold slope, while subthreshold operation realizes intrinsic exponential distance evaluation and linear voltage sensing ...
Hyung‐Jun Noh +4 more
wiley +1 more source
AE-MLP: A hybrid deep learning approach for DDoS detection and classification
, 2021 Distributed Denial-of-Service (DDoS) attacks are increasing as the demand for Internet connectivity massively grows in recent years. Conventional shallow machine learning-based techniques for DDoS attack classification tend to be ineffective when the ...
Yuanyuan Wei (233952) +5 more
core +1 more source
Scaling of solar wind e and the AU, AL and AE indices as seen by WIND [PDF]
, 2002 We apply the finite size scaling technique to quantify the statistical properties of fluctuations in AU, AL and AE indices and in the parameter that represents energy input from the solar wind into the magnetosphere. We find that the exponents needed to
Chapman, S.C. +8 more
core +2 more sources