Suchergebnisse - boosting adversarial autoencoder*

DBN-BAAE: Enhanced Lightweight Anomaly Detection Mechanism with Boosting Adversarial Autoencoder von Chen, Yanru, Wu, Bei, Zhong, Wang, Guo, Yanru, Wu, Dizhi, Ren, Yi, Zhang, Yuanyuan

“… To address these issues, this work introduces a deep belief network-based boosting adversarial autoencoder termed DBN-BAAE, a novel lightweight anomaly detection mechanism based on boosting adversarial …”
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scPER: A Rigorous Computational Approach to Determine Cellular Subtypes in Tumors Aligned With Cancer Phenotypes From Total RNA Sequencing von Li, Bingrui, Zhou, Xiaobo, Kalluri, Raghu

“… (Estimating cell Proportions using single-cell RNA-seq Reference), a rigorous approach combining adversarial autoencoder and extreme gradient boosting to estimate tumor …”
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Noise Reduction Power Stealing Detection Model Based on Self-Balanced Data Set von Liu, Haiqing, Li, Zhiqiao, Li, Yuancheng

“… ), Stacked Convolution Noise Reduction Autoencoder (SCDAE) and Lightweight Gradient Boosting Decision Machine (LightGBM …”
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Data augmentation for time series regression: Applying transformations, autoencoders and adversarial networks to electricity price forecasting von Demir, Sumeyra, Mincev, Krystof, Kok, Koen, Paterakis, Nikolaos G.

“… , can, however, counteract the restrictions imposed by small sample sizes: increasing a model’s robustness to overfitting and boosting out-of-sample prediction accuracies …”
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Kruskal Szekeres generative adversarial network augmented deep autoencoder for colorectal cancer detection von Krishnamoorthy, Suresh Kumar, Vanitha CN

“… The Kruskal Szekeres Generative Adversarial Network Augmented Deep Autoencoder (KSGANA-DA) is introduced for early colorectal cancer detection and it comprises two stages …”
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Unified multi-protocol MRI for Alzheimer’s disease diagnosis: Dual-decoder adversarial autoencoder and ensemble residual shrinkage attention network von Li, Shiyao, Lin, Shukuan, Tu, Yue, Qiao, Jianzhong, Xiao, Shenao

“… Specifically, we introduce a double decoder adversarial autoencoder (DDAAE) to align MRIs from different protocols …”
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LLM-AE-MP: Web Attack Detection Using a Large Language Model with Autoencoder and Multilayer Perceptron von Yang, Jing, Wu, Yuangui, Yuan, Yuping, Xue, Haozhong, Bourouis, Sami, Abdel-Salam, Mahmoud, Prajapat, Sunil, Por, Lip Yee

“… ) requests using an autoencoder (AE). The integration of AE allows for efficient feature distillation, enhancing the sensitivity of the model to anomalies in HTTP traffic …”
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Bringing realism: Enhancing high-dimensional data for active behavior analysis in older adults von Guo, Cong, Jiang, Yaoqin, Yang, Yitong, Yuan, Zhilu, Guo, Renzhong

“… To address these issues, a data generation algorithm is proposed based on 7631 data points from a case study of the household travel survey in Xiamen, China, comparing the Variational Autoencoder (VAE …”
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Synthetic Data Generation and Evaluation Techniques for Classifiers in Data Starved Medical Applications von Bae, Wan D., Alkobaisi, Shayma, Horak, Matthew, Bankar, Siddheshwari, Bhuvaji, Sartaj, Kim, Sungroul, Park, Choon-Sik

“… With their ability to find solutions among complex relationships of variables, machine learning (ML) techniques are becoming more applicable to various fields, …”
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Application of Machine Learning and Data Mining

“… The following special issue contains 14 articles accepted and published in the Special Issue "Mathematics and Computer Science, 2024" of the MDPI journal …”
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Generative hybrid models for fraud detection in auto insurance with a comparative analysis of VAE, GAN, and diffusion approaches von Bekkaye, Chadia, Oukhouya, Hassan, Zari, Tarek, Guerbaz, Raby, El Bouanani, Hicham

“… ), Generative Adversarial Networks (GANs), and Diffusion Models (DMs)—with an ensemble of classifiers including eXtreme Gradient Boosting (XGBoost), Random Forest (RF …”
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Hybrid Learning Models for IMU-Based HAR with Feature Analysis and Data Correction von Tseng, Yu-Hsuan, Wen, Chih-Yu

“… Referring to the experimental results, the proposed system selects the pre-trained eXtreme Gradient Boosting (XGBoost …”
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Industrial Control System Anomaly Detection and Classification Based on Network Traffic von Jiang, Jehn-Ruey, Chen, Yan-Ting

“… First, the denoising autoencoder (DAE) is utilized to reduce data noise and extract core features from data …”
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An Optimized Transformer–GAN–AE for Intrusion Detection in Edge and IIoT Systems: Experimental Insights from WUSTL-IIoT-2021, EdgeIIoTset, and TON_IoT Datasets von Salehiyan, Ahmad, Moghaddam, Pardis Sadatian, Kaveh, Masoud

“… The rapid expansion of Edge and Industrial Internet of Things (IIoT) systems has intensified the risk and complexity of cyberattacks. Detecting advanced …”
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An enhanced ensemble defense framework for boosting adversarial robustness of intrusion detection systems von Awad, Zeinab, Zakaria, Magdy, Hassan, Rasha

“… However, recent studies have revealed their vulnerability to adversarial attacks, where maliciously perturbed traffic samples can deceive trained DNN-based detectors, leading to incorrect …”
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Risk Estimation for Financial Contracts: Data Imbalance Elimination and Impact of Different Data Rates von Caliskan, Elif Ezel, Yildizak, Burak, Ozcan, Dogan, Salbacak, Gurbet Alpay, Vural, Ulas, Aydin, Tarkan

“… ), Adaptive Synthetic Sampling Approach for Imbalanced Learning (ADASYN), Tabular Variational Autoencoder (TVAE …”
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WarpDrive: Boosting Auto Loan Default Data Processing with GAN-Powered Data Augmentation and SAE-Based Rectification von Xueping, Zhu, Lin, Qin, Samuri, Suzani Mohamad, Adnan, Muhamad Hariz Muhamad

“… Accurately predicting loan defaults in automotive loan applications is crucial for financial institutions. However, imbalanced and anomalous datasets often …”
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WAVAE: A Weakly Augmented Variational Autoencoder for Time Series Anomaly Detection von Wu, Zhangkai, Zhang, Qi, Zhou, Junxian, Chen, Hui, Liu, Yanfang

“… In this work, we present WAVAE, a Weakly Augmented Variational Autoencoder that incorporates self-supervised learning (SSL …”
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Multiple imputation using the average code from autoencoders von Macias, Edwar, Serrano, Javier, Lopez Vicario, Jose, Morell, Antoni

“… •The computation of the average code from an autoencoder Improves the imputation of missing values …”
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Practical Guide to Machine Learning, NLP, and Generative AI: Libraries, Algorithms, and Applications von Mariprasath T, Rivera Marco, Cheepati Kumar Reddy

“… This hands-on guide explores the core concepts and cutting-edge techniques in machine learning, natural language processing (NLP), and generative AI. It covers …”
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