Search Results - stacked denoting sparse autoencoder

An Innovative Study for Tool Wear Prediction Based on Stacked Sparse Autoencoder and Ensemble Learning Strategy.

Authors: He, Zhaopeng Shi, Tielin Chen, Xu

Source: Sensors (14248220); Apr2025, Vol. 25 Issue 8, p2391, 14p

Subject Terms: ARTIFICIAL neural networks, MACHINE learning, ENSEMBLE learning, NUMERICAL control of machine tools, AUTOENCODERS, DEEP learning

SSAE‐KPLS: A quality‐related process monitoring via integrating stacked sparse autoencoder with kernel partial least squares.

Authors: Ye, Zhenyu Wu, Ping He, Yuchen et al.

Source: Canadian Journal of Chemical Engineering; Oct2023, Vol. 101 Issue 10, p5858-5873, 16p

Subject Terms: LEAST squares, FEATURE extraction, MANUFACTURING processes, PRODUCT quality

Optimal Deep Stacked Sparse Autoencoder Based Osteosarcoma Detection and Classification Model.

Authors: Fakieh, Bahjat AL-Ghamdi, Abdullah S. AL-Malaise Ragab, Mahmoud

Source: Healthcare (2227-9032); Jun2022, Vol. 10 Issue 6, p1040-1040, 18p

Subject Terms: OSTEOSARCOMA, COMPUTER-aided diagnosis, COMPUTER-assisted image analysis (Medicine), DEEP learning, BONE cancer

Weighted time series fault diagnosis based on a stacked sparse autoencoder.

Authors: Lv, Feiya Wen, Chenglin Liu, Meiqin et al.

Source: Journal of Chemometrics; Sep2017, Vol. 31 Issue 9, pn/a-N.PAG, 16p

Subject Terms: CHEMICAL industry, STATISTICS, FAULT diagnosis, THRESHOLDING algorithms, MULTIVARIATE analysis, NONLINEAR analysis

CT-Based Automatic Spine Segmentation Using Patch-Based Deep Learning.

Authors: Qadri, Syed Furqan Lin, Hongxiang Shen, Linlin et al.

Source: International Journal of Intelligent Systems; 3/4/2023, p1-14, 14p

Subject Terms: VERTEBRAL fractures, SPINE, STRUCTURAL optimization, SPINE abnormalities, IMAGE segmentation, DIAGNOSIS, DEEP learning

Construction of a Sensitive and Speed Invariant Gearbox Fault Diagnosis Model Using an Incorporated Utilizing Adaptive Noise Control and a Stacked Sparse Autoencoder-Based Deep Neural Network.

Authors: Nguyen, Cong Dai Prosvirin, Alexander E. Kim, Cheol Hong et al.

Source: Sensors (14248220); Jan2021, Vol. 21 Issue 1, p18, 1p

Subject Terms: FAULT diagnosis, NOISE control, ADAPTIVE control systems, GEARBOXES, NATURAL language processing

The Liver Meeting: 2025 Abstracts.

Source: Hepatology (02709139); 2025Supplement, Vol. 82, pS1-S2308, 2308p

Predictive Modeling With an Adaptive Unsupervised Broad Transfer Algorithm.

Authors: Liu, Guokai Shen, Weiming Gao, Liang et al.

Source: IEEE Transactions on Instrumentation & Measurement; 2021, Vol. 70, p1-12, 12p

Subject Terms: PREDICTION models, ALGORITHMS, CONCEPT learning, DATA distribution, SPARSE matrices, TECHNOLOGY transfer

Recognition of cognitive load with a stacking network ensemble of denoising autoencoders and abstracted neurophysiological features.

Authors: Cao, Zixuan Yin, Zhong Zhang, Jianhua

Source: Cognitive Neurodynamics; Jun2021, Vol. 15 Issue 3, p425-437, 13p

Using convolutional features and a sparse autoencoder for land-use scene classification.

Authors: Othman, Esam Bazi, Yakoub Alajlan, Naif et al.

Source: International Journal of Remote Sensing; May2016, Vol. 37 Issue 10, p2149-2167, 19p, 2 Color Photographs, 3 Diagrams, 2 Charts, 6 Graphs

Subject Terms: LAND use, NEURAL circuitry, MATHEMATICAL convolutions, SIGNAL convolution

Company/Entity: UNIVERSITY of California (System)

A DDoS-Attack Detection Method Oriented to the Blockchain Network Layer.

Authors: Dai, Qian-yi Zhang, Bin Dong, Shu-qin

Source: Security & Communication Networks; 5/4/2022, p1-18, 18p

Subject Terms: ARTIFICIAL neural networks, BLOCKCHAINS, CONVOLUTIONAL neural networks, TRAFFIC monitoring, DENIAL of service attacks, CONJUGATE gradient methods

Company/Entity: AMAZON Web Services Inc.

A Shilling Group Detection Framework Based on Deep Learning Techniques.

Authors: Wang, Shilei Zhang, Peng Wang, Hui et al.

Source: Security & Communication Networks; 6/30/2022, p1-16, 16p

Subject Terms: DEEP learning, RECOMMENDER systems, FEATURE extraction

Marginalized Multiview Ensemble Clustering.

Authors: Tao, Zhiqiang Liu, Hongfu Li, Sheng et al.

Source: IEEE Transactions on Neural Networks & Learning Systems; Feb2020, Vol. 31 Issue 2, p600-611, 12p

Subject Terms: INFORMATION commons, DATA corruption

Deep reinforcement learning navigation via decision transformer in autonomous driving.

Authors: Lun Ge Xiaoguang Zhou Yongqiang Li et al.

Source: Frontiers in Neurorobotics; 2024, p1-25, 25p

Subject Terms: REINFORCEMENT learning, DEEP reinforcement learning, TRANSFORMER models, PARTIALLY observable Markov decision processes, AUTONOMOUS vehicles, NAVIGATION

SDCA: a novel stack deep convolutional autoencoder – an application on retinal image denoising.

Authors: Ghosh, Swarup Kr Biswas, Biswajit Ghosh, Anupam

Source: IET Image Processing (Wiley-Blackwell); Dec2019, Vol. 13 Issue 14, p2778-2789, 12p

Machine-learning models for Alzheimer's disease diagnosis using neuroimaging data: survey, reproducibility, and generalizability evaluation.

Authors: Aghdam, Maryam Akhavan Bozdag, Serdar Saeed, Fahad

Source: Brain Informatics; 3/21/2025, Vol. 12 Issue 1, p1-27, 27p

Subject Terms: ALZHEIMER'S disease, MACHINE learning, DATA management, BRAIN imaging, GENERALIZABILITY theory, DIAGNOSIS, DEEP learning, REPRODUCIBLE research

Automated Radiology Report Generation: A Review of Recent Advances.

Authors: Sloan, Phillip Clatworthy, Philip Simpson, Edwin et al.

Source: IEEE Reviews in Biomedical Engineering; 2025, Vol. 18, p368-387, 20p

Deep learning informed diffusion equation model for image denoising.

Authors: Li, Yao Cheng, Li Guo, Zhichang et al.

Source: IET Image Processing (Wiley-Blackwell); 11/13/2024, Vol. 18 Issue 13, p4310-4327, 18p

Subject Terms: CONVOLUTIONAL neural networks, IMAGE denoising, PARTIAL differential equations, NONLINEAR differential equations, HEAT equation

Integration of Adversarial Autoencoders With Residual Dense Convolutional Networks for Estimation of Non-Gaussian Hydraulic Conductivities.

Authors: Shaoxing Mo Zabaras, Nicholas Xiaoqing Shi et al.

Source: Water Resources Research; Feb2020, Vol. 56 Issue 2, p1-24, 24p

Subject Terms: HYDRAULIC conductivity, FACIES, PHYSICS, PARAMETERIZATION

Deep Subspace Clustering.

Authors: Peng, Xi Feng, Jiashi Zhou, Joey Tianyi et al.

Source: IEEE Transactions on Neural Networks & Learning Systems; Dec2020, Vol. 31 Issue 12, p5509-5521, 13p

Subject Terms: DEEP learning, DEVELOPING countries, SUBSPACES (Mathematics), SPARSE matrices, IMAGE reconstruction