Výsledky vyhľadávania - "sparse autoencoder (SAE)"

Sparse Autoencoder (SAE) based Image Classification with Enhanced Security for College Attendance System

Autori: Sangeetha Karunakaran null Akila

Zdroj: 2024 4th International Conference on Mobile Networks and Wireless Communications (ICMNWC). :1-6

Power Quality Disturbances Classification Using Sparse Autoencoder (SAE) Based on Deep Neural Network

Autori: Nurul Asiah Manan Roslina Mohamad Shahrani Shahbudin a ďalší

Zdroj: 2021 IEEE 11th IEEE Symposium on Computer Applications & Industrial Electronics (ISCAIE). :19-22

Predmety: 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology, 7. Clean energy

Prístupová URL adresa: https://ieeexplore.ieee.org/abstract/document/9431822/

Wind Speed Prediction of Complex Terrain Based on Multi-Dimensional Time Series Decomposition

Autori: Jingru Sun Yao Zhang Yichuang Sun a ďalší

Zdroj: IEEE Access, Vol 13, Pp 206475-206489 (2025)

Predmety: Wind speed prediction, multivariate time series prediction (MTSP), sparse autoencoder (SAE), Kolmogorov–Arnold network (KAN), time series analysis, BiGRU, Electrical engineering. Electronics. Nuclear engineering, TK1-9971

Popis súboru: electronic resource

Relation: https://ieeexplore.ieee.org/document/11278174/; https://doaj.org/toc/2169-3536

Prístupová URL adresa: https://doaj.org/article/a96978cec89040f48b580902727118fd

Fault Diagnosis for Wind Turbine Gearboxes by Using Deep Enhanced Fusion Network

Autori: Ziqiang Pu Chuan Li Shaohui Zhang a ďalší

Prispievatelia: Ziqiang Pu Chuan Li Shaohui Zhang a ďalší

Zdroj: IEEE Transactions on Instrumentation and Measurement. 70:1-11

Predmety: Wind turbine gearbox, Sparse autoencoder (SAE), 0211 other engineering and technologies, 0202 electrical engineering, electronic engineering, information engineering, Echo state network (ESN), Feature enhancement, 02 engineering and technology, 7. Clean energy, Fault diagnosis

Popis súboru: application/pdf

Prístupová URL adresa: https://dblp.uni-trier.de/db/journals/tim/tim70.html#Pu0Z021
https://ieeexplore.ieee.org/document/9195827
https://hdl.handle.net/10400.1/17074

Intelligent Recognition of Insulator Contamination Grade Based on the Deep Learning of Ultraviolet Discharge Image Information

Autori: Da Zhang Shuailin Chen

Zdroj: Energies, Vol 13, Iss 5221, p 5221 (2020)

Predmety: noncontact detection, contamination grade, ultraviolet image, sparse autoencoder (SAE), deep belief network (DBN), Technology

Relation: https://www.mdpi.com/1996-1073/13/19/5221; https://doaj.org/toc/1996-1073; https://doaj.org/article/75c6c8f0a722406f81c4e3743e93a28e

Dostupnosť: https://doi.org/10.3390/en13195221
https://doaj.org/article/75c6c8f0a722406f81c4e3743e93a28e

Adaptive mobilenetv3 with spatial attention-aided effective brain tumor classification approach using denoised image-based segmentation.

Autori: Vijay, Kulkarni Sheetal Poornapushpakala, S.

Zdroj: International Journal of Innovative Research & Scientific Studies; 2025, Vol. 8 Issue 6, p157-179, 23p

Predmety: BRAIN tumors, CLASSIFICATION, IMAGE denoising, IMAGE segmentation, ATTENTION, CONVOLUTIONAL neural networks, MAGNETIC resonance imaging

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

Autori: Jo, Mi Young Kim, Hyun Jung

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

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

CoCoChain: A Concept-Aware Consensus Protocol for Secure Sensor Data Exchange in Vehicular Ad Hoc Networks.

Autori: Juárez, Rubén Nicolas-Sans, Ruben Tamames, José Fernández

Zdroj: Sensors (14248220); Oct2025, Vol. 25 Issue 19, p6226, 51p

Predmety: VEHICULAR ad hoc networks, BLOCKCHAINS, MOBILE communication systems, DATA transmission systems, DATA integrity, AUTOENCODERS

Coherent DOA estimation method based on angle interval separation learning. (English)

Autori: WANG, Jun WU, Zihan ZHOU, Guangjiao a ďalší

Zdroj: Systems Engineering & Electronics; Oct2025, Vol. 47 Issue 10, p3188-3198, 11p

Predmety: DIRECTION of arrival estimation, ARTIFICIAL neural networks, ESTIMATION theory, SIGNAL processing, DIMENSIONAL reduction algorithms, ANGULAR distance, COMPUTATIONAL complexity

Deep autoencoder-driven feature learning and meta-heuristic optimized machine learning modelling for crop water stress identification.

Autori: Subeesh, A. Chauhan, Naveen Chandel, Narendra Singh a ďalší

Zdroj: Evolving Systems; Sep2025, Vol. 16 Issue 3, p1-19, 19p

DEEP LEARNING-BASED FACE-IRIS RECOGNITION WITH CAPSULE NEURAL NETWORK (CAPSNET) FOR BIOMETRIC ATTENDANCE SYSTEM.

Autori: KARUNAKARAN, SANGEETHA AKILA, A.

Zdroj: TPM: Testing, Psychometrics, Methodology in Applied Psychology. 2025 Supplement, Vol. 32, p345-358. 14p.

Predmety: *CAPSULE neural networks, *IRIS recognition, *ARTIFICIAL neural networks, *BIOMETRY, *FACE perception, *DEEP learning

基于改进生成对抗网络和 Swin Transformer 的样本不均衡轴承故障诊断. (Chinese)

Alternate Title: Bearing fault diagnosis based on improved generative adversarial network and Swin Transformer under imbalanced sample conditions. (English)

Autori: 马良玉 黄日灏 段晓冲 a ďalší

Zdroj: Journal of Nanjing University of Information Science & Technology (Natural Science Edition) / Nanjing Xinxi Gongcheng Daxue Xuebao (ziran kexue ban); Jul2025, Vol. 17 Issue 4, p528-537, 10p

Predmety: CONVOLUTIONAL neural networks, GENERATIVE adversarial networks, TRANSFORMER models, FAULT diagnosis, DEEP learning

Automated multi-class skin cancer classification using white shark optimizer with ensemble learning classifier on dermoscopy images.

Autori: Arumugam, R. Vijay Saravanan, S.

Zdroj: Multimedia Tools & Applications; Mar2025, Vol. 84 Issue 8, p4857-4879, 23p

Predmety: ENSEMBLE learning, COMPUTER-aided diagnosis, ARTIFICIAL intelligence, DEEP learning, AUTOENCODERS

Out-of-Roundness Wheel Damage Identification in Railway Vehicles Using AutoEncoder Models.

Autori: Melo, Renato Finotti, Rafaelle Guedes, António a ďalší

Zdroj: Applied Sciences (2076-3417); Mar2025, Vol. 15 Issue 5, p2662, 25p

Predmety: STRUCTURAL health monitoring, AUTOENCODERS, RAILROAD safety measures, RAILROAD trains, COMPARATIVE studies

A COMPARATIVE STUDY OF DIVERSE AUTOENCODER MODELS IN LOCAL GEAR PITTING FAULT DIAGNOSIS.

Autori: YURTSEVER, Mustafa ÜMÜTLÜ, Rafet Can ÖZTÜRK, Hasan

Zdroj: Konya Journal of Engineering Sciences / Konya Mühendislik Bilimleri Dergisi; Mar2025, Vol. 13 Issue 1, p59-74, 16p

Predmety: GEARBOXES, FAULT diagnosis, POWER transmission, DEEP learning, AUTOENCODERS

iVRIDA-fleet: unsupervised rail vehicle running instability detection algorithm for passenger vehicle fleet.

Autori: Kulkarni, Rohan Berg, Mats Qazizadeh, Alireza a ďalší

Zdroj: Vehicle System Dynamics; Feb2025, Vol. 63 Issue 2, p277-307, 31p

Predmety: DETECTION algorithms, K-means clustering, PRINCIPAL components analysis, AUTOENCODERS, MECHANICAL wear

Type 2 diabetes prediction method based on dual-teacher knowledge distillation and feature enhancement.

Autori: Zhao, Jian Gao, Hanlin Sun, Lei a ďalší

Zdroj: Scientific Reports; 1/2/2025, Vol. 15 Issue 1, p1-15, 15p

Predmety: CONVOLUTIONAL neural networks, TYPE 2 diabetes, AUTOENCODERS, MEDICAL care costs, DIABETES

Dimensionality Reduction Strategies for Classification: ML Versus DL Approaches and Their Combinations.

Autori: Hung, Chihli Tsai, Chih‐Fong Wu, Ming‐Hui

Zdroj: Expert Systems. Oct2025, Vol. 42 Issue 10, p1-16. 16p.

Predmety: *CLASSIFICATION, *MACHINE learning, *AUTOENCODERS, *DIMENSIONAL reduction algorithms, *ENSEMBLE learning, *GENETIC algorithms, *DEEP learning, *FEATURE selection

A strategy for out-of-roundness damage wheels identification in railway vehicles based on sparse autoencoders.

Autori: Magalhães, Jorge Jorge, Tomás Silva, Rúben a ďalší

Zdroj: Railway Engineering Science; Dec2024, Vol. 32 Issue 4, p421-443, 23p

Predmety: RAILROAD trains, ARTIFICIAL neural networks, FEATURE extraction, AUTOMATIC identification, WHEELS, MULTISENSOR data fusion

Automated Kidney Cancer Classification using White Shark Optimizer with Ensemble Majority Voting Model on Pathology Images.

Autori: Althbiti, Ashrf

Zdroj: Fusion: Practice & Applications; 2025, Vol. 19 Issue 2, p418-433, 16p

Predmety: CONVOLUTIONAL neural networks, LONG short-term memory, RENAL cancer, WHITE shark, PLURALITY voting, DEAD, HEART assist devices