Výsledky vyhledávání - supervised sparse‐autoencoder‐based deep neural network

A Comparative Study of Lightweight, Sparse Autoencoder-Based Classifiers for Edge Network Devices: An Efficiency Analysis of Feed-Forward and Deep Neural Networks.

Autoři: Jo, Mi Young Kim, Hyun Jung

Zdroj: Sensors (14248220); Oct2025, Vol. 25 Issue 20, p6439, 22p

Témata: EDGE computing, AUTOENCODERS, RESEARCH evaluation, ANOMALY detection (Computer security), FEEDFORWARD neural networks, ARTIFICIAL neural networks

Sparse Autoencoder-based Multi-head Deep Neural Networks for Machinery Fault Diagnostics with Detection of Novelties

Autoři: Zhe Yang Dejan Gjorgjevikj Jianyu Long a další

Zdroj: Chinese Journal of Mechanical Engineering, Vol 34, Iss 1, Pp 1-12 (2021)

Témata: Deep learning, Fault diagnostics, Novelty detection, Multi-head deep neural network, Sparse autoencoder, Ocean engineering, TC1501-1800, Mechanical engineering and machinery, TJ1-1570

Popis souboru: electronic resource

Relation: https://doaj.org/toc/1000-9345; https://doaj.org/toc/2192-8258

Přístupová URL adresa: https://doaj.org/article/b89721cf6296483a8a2661e099c0789e

A deep learning framework for gender sensitive speech emotion recognition based on MFCC feature selection and SHAP analysis.

Autoři: Hu, Qingqing Peng, Yiran Zheng, Zhong

Zdroj: Scientific Reports; 8/5/2025, Vol. 15 Issue 1, p1-19, 19p

Témata: EMOTION recognition, DEEP learning, NATURAL language processing, RECURRENT neural networks, LONG short-term memory, CONVOLUTIONAL neural networks

Sparse Autoencoder-Based Multi-Head Deep Neural Networks for Machinery Fault Diagnostics With Novelty Detection

Autoři: Zhe Yang Dejan Gjorgjevikj Jian-Yu Long a další

Přístupová URL adresa: https://europepmc.org/article/PPR/PPR251499
https://www.researchsquare.com/article/rs-122416/v1.pdf
https://www.researchsquare.com/article/rs-122416/v1

A Comprehensive Review on Deep Learning Techniques in Alzheimer's Disease Diagnosis.

Autoři: Mahavar A Patel A

Zdroj: Current topics in medicinal chemistry [Curr Top Med Chem] 2025; Vol. 25 (4), pp. 335-349.

Způsob vydávání: Journal Article; Review

Informace o časopise: Publisher: Bentham Science Publishers Country of Publication: United Arab Emirates NLM ID: 101119673 Publication Model: Print Cited Medium: Internet ISSN: 1873-4294 (Electronic) Linking ISSN: 15680266 NLM ISO Abbreviation: Curr Top Med Chem Subsets: MEDLINE

Výrazy ze slovníku MeSH: Alzheimer Disease*/diagnosis , Deep Learning*, Humans ; Biomarkers/analysis ; Neural Networks, Computer

Sparse Autoencoder-based Multi-head Deep Neural Networks for Machinery Fault Diagnostics with Detection of Novelties.

Autoři: Yang, Zhe Gjorgjevikj, Dejan Long, Jianyu a další

Zdroj: Chinese Journal of Mechanical Engineering; 6/4/2021, Vol. 34 Issue 1, p1-12, 12p

Gear Fault Detection Method Based on Convex Hull Clustering of Autoencoder's Latent Space.

Autoři: Batsch, Michał Kiczek, Bartłomiej

Zdroj: Applied Sciences (2076-3417); Jun2024, Vol. 14 Issue 12, p5282, 21p

Témata: ARTIFICIAL neural networks, GENERATIVE adversarial networks, SUPERVISED learning, PRINCIPAL components analysis, SIGNAL processing, MACHINE learning

Deep autoencoder based domain adaptation for transfer learning.

Autoři: Dev, Krishna Ashraf, Zubair Muhuri, Pranab K. a další

Zdroj: Multimedia Tools & Applications; Jul2022, Vol. 81 Issue 16, p22379-22405, 27p

Témata: SUPERVISED learning, TRANSFER of training, ARTIFICIAL neural networks, DEEP learning, PHYSIOLOGICAL adaptation, MACHINE learning, CONCEPT learning

Sparse Representation Convolutional Autoencoder for Feature Learning of Vibration Signals and its Applications in Machinery Fault Diagnosis.

Autoři: Miao, Mengqi Sun, Yuanhang Yu, Jianbo

Zdroj: IEEE Transactions on Industrial Electronics; Dec2022, Vol. 69 Issue 12, p13565-13575, 11p

Témata: ROLLER bearings, FAULT diagnosis, ARTIFICIAL neural networks, SUPERVISED learning, DEEP learning, VIBRATION (Mechanics), MACHINERY

Robust approach for AMC in frequency selective fading scenarios using unsupervised sparse‐autoencoder‐based deep neural network.

Autoři: Shah, Maqsood Hussain Dang, Xiaoyu

Zdroj: IET Communications (Wiley-Blackwell); Mar2019, Vol. 13 Issue 4, p423-432, 10p

Témata: ARTIFICIAL neural networks, ARTIFICIAL intelligence, DEEP learning, ORDER statistics, SIGNAL classification

A comparative case study between shallow and deep neural networks in induction motor's fault diagnosis.

Autoři: Gholaminejad, Azadeh Jorkesh, Saeid Poshtan, Javad

Zdroj: IET Science, Measurement & Technology (Wiley-Blackwell); Jul2023, Vol. 17 Issue 5, p195-207, 13p

Témata: ARTIFICIAL neural networks, INDUCTION motors, FAULT diagnosis, INDEPENDENT component analysis, SHORT circuits, POWER resources

A heterogeneous graph convolutional attention network method for classification of autism spectrum disorder.

Autoři: Shao, Lizhen Fu, Cong Chen, Xunying

Zdroj: BMC Bioinformatics; 9/27/2023, Vol. 24 Issue 1, p1-17, 17p

Témata: AUTISM spectrum disorders, ARTIFICIAL neural networks, FUNCTIONAL magnetic resonance imaging, FEATURE extraction, DEEP learning

Reliable Fault Diagnosis of Rotary Machine Bearings Using a Stacked Sparse Autoencoder-Based Deep Neural Network.

Autoři: Sohaib, Muhammad Kim, Jong-Myon

Zdroj: Shock & Vibration; 5/7/2018, p1-11, 11p

Témata: ROTARY combustion engines, FAULT diagnosis, NEURAL circuitry, COST effectiveness, ALGORITHMS

A Multistage Physics-Informed Neural Network for Fault Detection in Regulating Valves of Nuclear Power Plants.

Autoři: Lai, Chenyang Ahmed, Ibrahim Zio, Enrico a další

Zdroj: Energies (19961073); Jun2024, Vol. 17 Issue 11, p2647, 23p

Témata: NUCLEAR power plants, RELIEF valves, ARTIFICIAL neural networks, FLOW coefficient, VALVES, VECTOR data

Deep Learning in Aircraft Design, Dynamics, and Control: Review and Prospects.

Autoři: Dong, Yiqun Tao, Jun Zhang, Youmin a další

Zdroj: IEEE Transactions on Aerospace & Electronic Systems; Aug2021, Vol. 57 Issue 4, p2346-2368, 23p

Témata: DEEP learning, OBJECT recognition (Computer vision), RECURRENT neural networks, FLIGHT control systems, CONVOLUTIONAL neural networks, PROBLEM solving

Deep Neural Network for Robust Modulation Classification Under Uncertain Noise Conditions.

Autoři: Hu, Shisheng Pei, Yiyang Liang, Paul Pu a další

Zdroj: IEEE Transactions on Vehicular Technology; Jan2020, Vol. 69 Issue 1, p564-577, 14p

Témata: RECURRENT neural networks, CONDITIONAL expectations, ARTIFICIAL neural networks, NOISE, COMPUTATIONAL complexity

Data‐driven sensor fault detection and isolation of nonlinear systems: Deep neural‐network Koopman operator.

Autoři: Bakhtiaridoust, Mohammadhosein Irani, Fatemeh Negar Yadegar, Meysam a další

Zdroj: IET Control Theory & Applications (Wiley-Blackwell); Jan2023, Vol. 17 Issue 2, p123-132, 10p

Témata: NONLINEAR systems, FAULT diagnosis, LINEAR operators, INVARIANT sets, DETECTORS, SET functions

A deep neural network for the classification of epileptic seizures using hierarchical attention mechanism.

Autoři: Chirasani, Sateesh Kumar Reddy Manikandan, Suchetha

Zdroj: Soft Computing - A Fusion of Foundations, Methodologies & Applications; Jun2022, Vol. 26 Issue 11, p5389-5397, 9p

Témata: EPILEPSY, DEEP learning, FEATURE extraction, COMPUTATIONAL complexity

A hybrid deep neural network based prediction of 300 MW coal-fired boiler combustion operation condition.

Autoři: Han, ZheZhe Huang, YiZhi Li, Jian a další

Zdroj: SCIENCE CHINA Technological Sciences; Oct2021, Vol. 64 Issue 10, p2300-2311, 12p

Seven-layer deep neural network based on sparse autoencoder for voxelwise detection of cerebral microbleed.

Autoři: Zhang, Yu-Dong Zhang, Yin Hou, Xiao-Xia a další

Zdroj: Multimedia Tools & Applications; May2018, Vol. 77 Issue 9, p10521-10538, 18p

Témata: ARTIFICIAL neural networks, VOXEL-based morphometry, CEREBRAL circulation, SIMULATION methods & models, GLOMERULAR filtration rate, PHYSIOLOGY