Výsledky vyhľadávania - Reduced deep conventional stack autoencoder~

Precise single step and multistep short-term photovoltaic parameters forecasting based on reduced deep convolutional stack autoencoder and minimum variance multikernel random vector functional network.

Autori: Sahani, Mrutyunjaya Choudhury, Sasmita Siddique, Marif Daula a ďalší

Zdroj: Engineering Applications of Artificial Intelligence. Oct2024:Part A, Vol. 136, pN.PAG-N.PAG. 1p.

Predmety: *FIELD programmable gate arrays, *SOLAR temperature, *SOLAR power plants, *STATISTICAL correlation, *ENERGY shortages

Epileptic Seizure Recognition Using Reduced Deep Convolutional Stack Autoencoder and Improved Kernel RVFLN From EEG Signals.

Autori: Sahani, Mrutyunjaya Rout, Susanta Kumar Dash, Pradipta Kishor

Zdroj: IEEE Transactions on Biomedical Circuits & Systems; Jun2021, Vol. 16 Issue 3, p595-605, 11p

An Efficient Mutual Authentication and Fractional Lyrebird Optimization With Deep Learning–Based SIP‐Based DRDoS Attack Detection.

Autori: Sreenivasulu, V. Ravikumar, C. V. Poruran, Sivakumar

Zdroj: International Journal of Distributed Sensor Networks; 8/7/2025, Vol. 2025, p1-24, 24p

Predmety: DEEP learning, DENIAL of service attacks, INTRUSION detection systems (Computer security), SECURITY management, ELECTRONIC authentication, OPTIMIZATION algorithms, SESSION Initiation Protocol (Computer network protocol)

A Hybrid Forecasting System Based on Comprehensive Feature Selection and Intelligent Optimization for Stock Price Index Forecasting.

Autori: He, Xuecheng Wang, Jujie

Zdroj: Mathematics (2227-7390); Dec2024, Vol. 12 Issue 23, p3778, 25p

Predmety: STOCK price forecasting, STOCK price indexes, STANDARD deviations, KRIGING, AUTOENCODERS

DSSAE-BBOA: deep learning-based weather big data analysis and visualization.

Autori: G, Madhukar Rao Dharavath, Ramesh

Zdroj: Multimedia Tools & Applications; 7/25/2021, p27471-27493, 23p

Predmety: BIG data, DATA visualization, FEATURE selection, DATA analysis, WEATHER

Incorporating Heterogeneous Features into the Random Subspace Method for Bearing Fault Diagnosis.

Autori: Chu, Yan Ali, Syed Muhammad Lu, Mingfeng a ďalší

Zdroj: Entropy; Aug2023, Vol. 25 Issue 8, p1194, 23p

Predmety: FAULT diagnosis, FEATURE extraction, PLURALITY voting, SIGNAL processing, MACHINE learning

Korporácia: CASE Western Reserve University

NRDPU-Net: A Normalized Residual Depth U-Net with Ridge Vessel Preprocessing for Accurate Melanoma Classification

Autori: Shyamala Devi, M Natarajan, Yuvaraj K. R., Sri Preethaa

A Sintering State Recognition Framework to Integrate Prior Knowledge and Hidden Information Considering Class Imbalance.

Autori: Wang, Dingxiang Zhang, Xiaogang Chen, Hua a ďalší

Zdroj: IEEE Transactions on Industrial Electronics; Aug2021, Vol. 68 Issue 8, p7400-7411, 12p

Predmety: PRIOR learning, SINTERING, FEATURE extraction, KERNEL functions

Indian classical musical instrument classification using Timbral features.

Autori: Gulhane, Sushen Rameshpant Shirbahadurkar, Suresh Damodar Badhe, Sanjay Shrikrushna

Zdroj: Concurrency & Computation: Practice & Experience; 11/10/2021, Vol. 33 Issue 21, p1-19, 19p

Predmety: MUSICAL instruments, MUSICOLOGY, WEIGHT training, FOURIER transforms, CLASSIFICATION

FPGA-Based Semisupervised Multifusion RDCNN of Process Robust VMD Data With Online Kernel RVFLN for Power Quality Events Recognition.

Autori: Sahani, Mrutyunjaya Dash, Pradipta Kishore

Zdroj: IEEE Transactions on Neural Networks & Learning Systems; Feb2022, Vol. 33 Issue 2, p515-527, 13p

Predmety: CONVOLUTIONAL neural networks, PARTICLE swarm optimization, FIELD programmable gate arrays, FEATURE extraction, MATHEMATICAL optimization

Autoencoder-based confidence score for item preknowledge detection.

Autori: Pan, Yiqin

Zdroj: Behaviormetrika; Jul2025, Vol. 52 Issue 2, p317-342, 26p

Predmety: AUTOENCODERS, DEEP learning, PRIOR learning, SIMULATION methods & models, DETECTION algorithms, SIGNAL detection, TEST design

From Innovation to Application: Can Emerging Imaging Techniques Transform Breast Cancer Diagnosis?

Autori: Hsu, Honda Lee, Kun-Hua Karmakar, Riya a ďalší

Zdroj: Diagnostics (2075-4418); Nov2025, Vol. 17 Issue 21, p2718, 48p

Predmety: BREAST cancer, DIAGNOSTIC imaging, MACHINE learning, DEEP learning, CLINICAL trials

Stacked Autoencoders Driven by Semi-Supervised Learning for Building Extraction from near Infrared Remote Sensing Imagery.

Autori: Protopapadakis, Eftychios Doulamis, Anastasios Doulamis, Nikolaos a ďalší

Zdroj: Remote Sensing; Feb2021, Vol. 13 Issue 3, p371, 1p

Predmety: REMOTE sensing, OPTICAL radar, LIDAR, INFRARED imaging, SUPERVISED learning, ESTIMATION theory, SECURE Sockets Layer (Computer network protocol)

Geografický termín: GERMANY

An Integrated Hybrid Deep Learning Framework for Intrusion Detection in IoT and IIoT Networks Using CNN-LSTM-GRU Architecture.

Autori: Afraji, Doaa Mohsin Abd Ali Lloret, Jaime Peñalver, Lourdes

Zdroj: Computation; Sep2025, Vol. 13 Issue 9, p222, 28p

Predmety: INTRUSION detection systems (Computer security), DEEP learning, ELECTRONIC data processing, INTERNET security, INTERNET of things

Automatic fault diagnosis of rolling bearings under multiple working conditions based on unsupervised stack denoising autoencoder.

Autori: Wang, Lei Rao, Hang Dong, Zhengcheng a ďalší

Zdroj: Structural Health Monitoring; Sep2024, Vol. 23 Issue 5, p3084-3104, 21p

Predmety: AUTOENCODERS, DEEP learning, ROLLER bearings, DIAGNOSIS, ALGORITHMS, FEATURE extraction

A Hybrid Ensemble Learning Framework for Predicting Lumbar Disc Herniation Recurrence: Integrating Supervised Models, Anomaly Detection, and Threshold Optimization.

Autori: Duceac, Mădălina Buzea, Călin Gheorghe Pleșea-Condratovici, Alina a ďalší

Zdroj: Diagnostics (2075-4418); Jul2025, Vol. 15 Issue 13, p1628, 40p

Predmety: ARTIFICIAL neural networks, ENSEMBLE learning, CLINICAL decision support systems, AUTOENCODERS, BLENDED learning

Conventional to Deep Learning Methods for Hyperspectral Unmixing: A Review.

Autori: Zou, Jinlin Qu, Hongwei Zhang, Peng

Zdroj: Remote Sensing; Sep2025, Vol. 17 Issue 17, p2968, 44p

Predmety: DEEP learning, REMOTE sensing, ALGORITHMS, METADATA, IMAGE processing, IMAGE reconstruction algorithms

Conventional machine learning and deep learning in Alzheimer's disease diagnosis using neuroimaging: A review.

Autori: Zhen Zhao Joon Huang Chuah Khin Wee Lai a ďalší

Zdroj: Frontiers in Computational Neuroscience; 2/6/2023, Vol. 17, p1-16, 16p

Predmety: DEEP learning, ALZHEIMER'S disease, MACHINE learning, DIAGNOSIS, MAGNETIC resonance imaging, CONVOLUTIONAL neural networks

Introducing a microstructure-embedded autoencoder approach for reconstructing high-resolution solution field data from a reduced parametric space.

Autori: Najafi Koopas, Rasoul Rezaei, Shahed Rauter, Natalie a ďalší

Zdroj: Computational Mechanics; Apr2025, Vol. 75 Issue 4, p1377-1406, 30p

Predmety: ARTIFICIAL neural networks, AUTOENCODERS, BOUNDARY value problems, ARTIFICIAL intelligence, THERMAL conductivity

Developments in Deep Learning Artificial Neural Network Techniques for Medical Image Analysis and Interpretation.

Autori: Shobayo, Olamilekan Saatchi, Reza

Zdroj: Diagnostics (2075-4418); May2025, Vol. 15 Issue 9, p1072, 31p

Predmety: ARTIFICIAL neural networks, PATTERN recognition systems, ARTIFICIAL intelligence, TRANSFORMER models, GENERATIVE adversarial networks