Suchergebnisse - stacked denoising autoencoder(SADE)

A novel multimodal framework for automatic recognition of individual cattle based on hybrid features using sparse stacked denoising autoencoder and group sparse representation techniques.

Autoren: Kumar, Santosh Kumar, Sunil Shafi, Mehak et al.

Quelle: Multimedia Tools & Applications; Sep2022, Vol. 81 Issue 21, p31075-31106, 32p

Schlagwörter: ENDANGERED species, FEATURE extraction, FACE, EXTRACTION techniques

Power transformer fault warning combining support vector machine and improved grey wolf optimization algorithm.

Autoren: SHUZONG ZHAO NORASAGE PATTANADECH

Quelle: Archives of Electrical Engineering; 2025, Vol. 74 Issue 1, p191-208, 18p

Schlagwörter: OPTIMIZATION algorithms, PARTICLE swarm optimization, POWER transformers, FAULT diagnosis, AUTOENCODERS, MACHINE performance

Remote Sensing Image Classification Based on Stacked Denoising Autoencoder.

Autoren: Liang, Peng Shi, Wenzhong Zhang, Xiaokang

Quelle: Remote Sensing; Jan2018, Vol. 10 Issue 1, p16, 12p

Schlagwörter: SIGNAL denoising, REMOTE sensing, ERROR probability, BACK propagation, LAND cover

Visual tracking based on stacked Denoising Autoencoder network with genetic algorithm optimization.

Autoren: Hua, Weixin Mu, Dejun Guo, Dawei et al.

Quelle: Multimedia Tools & Applications; Feb2018, Vol. 77 Issue 4, p4253-4269, 17p

Schlagwörter: TRACKING & trailing, SIGNAL denoising, GENETIC algorithm software, MATHEMATICAL optimization, MONTE Carlo method software, OBJECT tracking (Computer vision)

基于火焰成像和堆栈降噪 自编码的燃烧工况识别. (Chinese)

Alternate Title: Combustion condition identification through flame imaging and stacked denoising autoencoder. (English)

Autoren: 韩哲哲 段德智 倪浩伟 et al.

Quelle: Journal of Southeast University / Dongnan Daxue Xuebao; May2020, Vol. 50 Issue 3, p537-544, 8p

A Robust Acoustic Feature Extraction Approach Based on Stacked Denoising Autoencoder.

Autoren: Liu, J.H. Zheng, W.Q. Zou, Y.X.

Quelle: 2015 IEEE International Conference on Multimedia Big Data; 2015, p124-127, 4p

Inverter Fault Diagnosis for a Three-Phase Permanent-Magnet Synchronous Motor Drive System Based on SDAE-GAN-LSTM.

Autoren: Feng, Li Luo, Honglin Xu, Shuiqing et al.

Quelle: Electronics (2079-9292); Oct2023, Vol. 12 Issue 19, p4172, 21p

Schlagwörter: FAULT diagnosis, SYNCHRONOUS electric motors, INDUCTION machinery, GENERATIVE adversarial networks, PERMANENT magnet motors, SHORT-term memory, ELECTRIC fault location, DIAGNOSTIC errors

Intelligent Compensation Method of Infrared Temperature Measurement for Multiple Interference Factors.

Autoren: Pan, Dong Jiang, Zhaohui Li, Yitian et al.

Quelle: IEEE Sensors Journal; 10/1/2022, Vol. 22 Issue 19, p18550-18559, 10p

PRPI-SC: an ensemble deep learning model for predicting plant lncRNA-protein interactions.

Autoren: Zhou, Haoran Wekesa, Jael Sanyanda Luan, Yushi et al.

Quelle: BMC Bioinformatics; 8/24/2021 Supplement 3, Vol. 22, p1-14, 14p

Schlagwörter: DEEP learning, CONVOLUTIONAL neural networks, RNA-binding proteins, PLANT proteins, PROTEIN-protein interactions

Breast cancer cell nuclei classification in histopathology images using deep neural networks.

Autoren: Feng, Yangqin Zhang, Lei Yi, Zhang

Quelle: International Journal of Computer Assisted Radiology & Surgery; Feb2018, Vol. 13 Issue 2, p179-191, 13p

An Overview of the Latest Developments and Potential Paths for Artificial Intelligence in Wastewater Treatment Systems.

Autoren: Sun, Wenquan Gao, Yun Zhou, Jun et al.

Quelle: Water (20734441); Aug2025, Vol. 17 Issue 16, p2432, 21p

Schlagwörter: ARTIFICIAL intelligence, WASTEWATER treatment, PROCESS optimization, WASTE treatment, DEEP learning, TECHNOLOGICAL innovations, ARTIFICIAL neural networks, WATER quality monitoring

3T dilated inception network for enhanced autism spectrum disorder diagnosis using resting-state fMRI data.

Autoren: Kavitha, V. Siva, R.

Quelle: Cognitive Neurodynamics; 2025, Vol. 19 Issue 1, p1-21, 21p

Research on the Identification of Pilots' Fatigue Status Based on Functional Near-Infrared Spectroscopy.

Autoren: Pan, Ting Wang, Haibo Si, Haiqing et al.

Quelle: Aerospace (MDPI Publishing); Mar2022, Vol. 9 Issue 3, p173, 1p

Schlagwörter: NEAR infrared spectroscopy, FISHER discriminant analysis, FATIGUE (Physiology), SUPPORT vector machines, OXYHEMOGLOBIN, STANDARD deviations

A novel denoising autoencoder hybrid network for remaining useful life estimation of lithium‐ion batteries.

Autoren: Xia, Wei Xu, Jinli Liu, Baolei et al.

Quelle: Energy Science & Engineering; Aug2024, Vol. 12 Issue 8, p3390-3400, 11p

Schlagwörter: REMAINING useful life, CONVOLUTIONAL neural networks, DATA libraries, LITHIUM cells, ELECTRIC vehicles

Fault detection and recognition of multivariate process based on feature learning of one-dimensional convolutional neural network and stacked denoised autoencoder.

Autoren: Zhang, Chengyi Yu, Jianbo Wang, Shijin

Quelle: International Journal of Production Research; Apr2021, Vol. 59 Issue 8, p2426-2449, 24p, 2 Color Photographs, 3 Diagrams, 15 Charts, 4 Graphs

Schlagwörter: CONVOLUTIONAL neural networks, SIGNAL convolution, FAULT diagnosis, ARTIFICIAL neural networks, MANUFACTURING processes, SIGNAL processing, DEEP learning, CONVEYOR belts

Gearbox Fault Diagnosis Based on Optimized Stacked Denoising Auto Encoder and Kernel Extreme Learning Machine.

Autoren: Wu, Zhenghao Yan, Hao Zhan, Xianbiao et al.

Quelle: Processes; Jul2023, Vol. 11 Issue 7, p1936, 20p

Schlagwörter: GEARBOXES, FAULT diagnosis, MACHINE learning, PARTICLE swarm optimization, HEBBIAN memory, FEATURE extraction

Leveraging Wearable Sensors for Human Daily Activity Recognition with Stacked Denoising Autoencoders.

Autoren: Ni, Qin Fan, Zhuo Zhang, Lei et al.

Quelle: Sensors (14248220); Sep2020, Vol. 20 Issue 18, p5114, 1p

Schlagwörter: HUMAN activity recognition, GYROSCOPES, IMAGE denoising, DETECTORS, DEEP learning

An efficient deep neural model for detecting crowd anomalies in videos.

Autoren: Yang, Meng Tian, Shucong Rao, Aravinda S. et al.

Quelle: Applied Intelligence; Jun2023, Vol. 53 Issue 12, p15695-15710, 16p

Schlagwörter: CONVOLUTIONAL neural networks, IMAGE denoising, VIDEO surveillance, SUPPORT vector machines, DEEP learning, REINFORCEMENT learning, MARKOV processes, CROWDS

Cyborg Moth Flight Control Based on Fuzzy Deep Learning.

Autoren: Yang, Xiao Jiang, Xun-Lin Su, Zheng-Lian et al.

Quelle: Micromachines; Apr2022, Vol. 13 Issue 4, pN.PAG-N.PAG, 18p

Schlagwörter: CYBORGS, DEEP learning, MOTHS, INSECT pest control

A fault diagnosis method based on Auxiliary Classifier Generative Adversarial Network for rolling bearing.

Autoren: Wu, Chunming Zeng, Zhou

Quelle: PLoS ONE; 3/1/2021, Vol. 16 Issue 3, p1-21, 21p

Schlagwörter: FAULT diagnosis, GENERATIVE adversarial networks, ROLLER bearings, DIAGNOSIS, PROBLEM solving, NOISE pollution