Search Results - 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.

Authors: Sahani, Mrutyunjaya Choudhury, Sasmita Siddique, Marif Daula et al.

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

Subject Terms: *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.

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

Source: 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.

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

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

Subject Terms: 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.

Authors: He, Xuecheng Wang, Jujie

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

Subject Terms: STOCK price forecasting, STOCK price indexes, STANDARD deviations, KRIGING, AUTOENCODERS

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

Authors: G, Madhukar Rao Dharavath, Ramesh

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

Subject Terms: BIG data, DATA visualization, FEATURE selection, DATA analysis, WEATHER

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

Authors: Chu, Yan Ali, Syed Muhammad Lu, Mingfeng et al.

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

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

Company/Entity: CASE Western Reserve University

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

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

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

Authors: Wang, Dingxiang Zhang, Xiaogang Chen, Hua et al.

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

Subject Terms: PRIOR learning, SINTERING, FEATURE extraction, KERNEL functions

Indian classical musical instrument classification using Timbral features.

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

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

Subject Terms: 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.

Authors: Sahani, Mrutyunjaya Dash, Pradipta Kishore

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

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

Autoencoder-based confidence score for item preknowledge detection.

Authors: Pan, Yiqin

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

Subject Terms: 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?

Authors: Hsu, Honda Lee, Kun-Hua Karmakar, Riya et al.

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

Subject Terms: 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.

Authors: Protopapadakis, Eftychios Doulamis, Anastasios Doulamis, Nikolaos et al.

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

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

Geographic Terms: GERMANY

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

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

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

Subject Terms: 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.

Authors: Wang, Lei Rao, Hang Dong, Zhengcheng et al.

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

Subject Terms: 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.

Authors: Duceac, Mădălina Buzea, Călin Gheorghe Pleșea-Condratovici, Alina et al.

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

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

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

Authors: Zou, Jinlin Qu, Hongwei Zhang, Peng

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

Subject Terms: 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.

Authors: Zhen Zhao Joon Huang Chuah Khin Wee Lai et al.

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

Subject Terms: 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.

Authors: Najafi Koopas, Rasoul Rezaei, Shahed Rauter, Natalie et al.

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

Subject Terms: 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.

Authors: Shobayo, Olamilekan Saatchi, Reza

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

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