Search Results - stack autoencoder*

SDAEDVSR: Efficient Video Super-Resolution With Stack Dense AutoEncoder

Authors: Ming Cao

Source: 2025 2nd International Conference on Electronic Engineering and Information Systems (EEISS). :1-5

Classification method for imbalanced LiDAR point cloud based on stack autoencoder

Authors: Peng Ren Qunli Xia

Source: Electronic Research Archive, Vol 31, Iss 6, Pp 3453-3470 (2023)

Subject Terms: T57-57.97, lidar point cloud, Applied mathematics. Quantitative methods, oversampling, imbalanced classification, deep neural network, QA1-939, stack autoencoder, Mathematics

Access URL: https://doaj.org/article/9970255490c2435c9d3acc6171ba6d49

Comparative Analysis of DNA LLM Classification Techniques Using Intra-Layer Feature Extraction with Autoencoder Stacks

Authors: Garret Obenchain

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

Authors: Lei Wang Hang Rao Zhengcheng Dong et al.

Source: Structural Health Monitoring. 23:3084-3104

Subject Terms: 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology

Triple Stack Deep Variational Autoencoder For Improved Hand Gesture Recognition

Authors: Arti Bahuguna Gopa Bhaumik Mahesh Chandra Govil

Source: 2024 15th International Conference on Computing Communication and Networking Technologies (ICCCNT). :1-7

A Multiobjective Autoencoder Deep Learning-Based Stack Switching Scheme for Enhanced Battery Life and Error Prediction in Wind-Battery

Authors: Niranjan Nayak ANSHUMAN Satpathy Satish Choudhury

Stack Denoising Autoencoder and State-Space Model Based Bearing RUL Prediction Method

Authors: Lei Yang Cuiwentong Xu Rongkai Duan et al.

Source: 2022 International Conference on Sensing, Measurement & Data Analytics in the era of Artificial Intelligence (ICSMD). :1-6

A Fault Diagnosis Method for Photovoltaic Arrays Based on Dropout Optimized Stack Autoencoders

Authors: Wei Chen Zhuanping Jiang Tingting Pei et al.

Source: 2022 IEEE 6th Conference on Energy Internet and Energy System Integration (EI2). :78-83

Vehicle type classification using graph ant colony optimizer based stack autoencoder model

Authors: B. Kavitha Rani M. Varaprasad Rao Raj Kumar Patra et al.

Source: Multimedia Tools and Applications. 81:42163-42182

Subject Terms: 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology

Stack Autoencoder Transfer Learning Algorithm for Bearing Fault Diagnosis Based on Class Separation and Domain Fusion

Authors: Meidi Sun Hui Wang Ping Liu et al.

Source: IEEE Transactions on Industrial Electronics. 69:3047-3058

Subject Terms: 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology

Access URL: https://ieeexplore.ieee.org/document/9384191

Fault Diagnosis of Rolling Bearings Based on an Improved Stack Autoencoder and Support Vector Machine

Authors: Mingliang Cui Youqing Wang Xinshuang Lin et al.

Source: IEEE Sensors Journal. 21:4927-4937

Subject Terms: 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology, 01 natural sciences, 0104 chemical sciences

Access URL: https://ieeexplore.ieee.org/document/9223764/
https://ui.adsabs.harvard.edu/abs/2021ISenJ..21.4927C/abstract

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

Authors: Mrutyunjaya Sahani Susanta Kumar Rout Pradipta Kishor Dash

Source: IEEE Transactions on Biomedical Circuits and Systems. 15:595-605

Subject Terms: Epilepsy, Seizures, 0202 electrical engineering, electronic engineering, information engineering, Humans, Electroencephalography, Signal Processing, Computer-Assisted, Neural Networks, Computer, 02 engineering and technology, Child, Algorithms

Access URL: https://pubmed.ncbi.nlm.nih.gov/34156948
https://ieeexplore.ieee.org/document/9462442/
https://europepmc.org/article/MED/34156948

Deep Convolutional Stack Autoencoder of Process Adaptive VMD Data With Robust Multikernel RVFLN for Power Quality Events Recognition

Authors: Mrutyunjaya Sahani Pradipta Kishore Dash

Source: IEEE Transactions on Instrumentation and Measurement. 70:1-12

Subject Terms: 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology

Access URL: https://ieeexplore.ieee.org/document/9335941
http://ieeexplore.ieee.org/iel7/19/9259274/09335941.pdf
https://dblp.uni-trier.de/db/journals/tim/tim70.html#SahaniD21

A Stack Autoencoders Based Deep Neural Network Approach for Cervical Cell Classification in Pap-Smear Images

Authors: Kumar Singh Sanjay Goyal Anjali

Source: Recent Advances in Computer Science and Communications. 14:62-70

Subject Terms: 0301 basic medicine, 0303 health sciences, 03 medical and health sciences, 3. Good health

Access URL: https://www.eurekaselect.com/170698/article

Intelligent Pre-warning Method of Transmission Line Icing Based on Stack Denoising Autoencoder

Authors: Chunyi Wang Wei Liu Heng Zhou et al.

Source: Lecture Notes in Electrical Engineering ISBN: 9789819938872

Adaptive hybrid optimization enabled stack autoencoder-based MapReduce framework for big data classification

Authors: S.Md. Mujeeb K. Madhavi R. Praveen Sam

Source: 2020 International Conference on Emerging Trends in Information Technology and Engineering (ic-ETITE). :1-5

Subject Terms: 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology

Access URL: https://jglobal.jst.go.jp/en/detail?JGLOBAL_ID=202002277794259561

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: Mrutyunjaya Sahani Sasmita Choudhury Marif Daula Siddique et al.

Source: Engineering Applications of Artificial Intelligence. 136:108935

Predicting chemical structure using reinforcement learning with a stack-augmented conditional variational autoencoder

Authors: Hwanhee Kim Soohyun Ko Byung Ju Kim et al.

Source: Journal of Cheminformatics, Vol 14, Iss 1, Pp 1-12 (2022)

Subject Terms: De novo drug design, Reinforcement learning, Conditional Variational AutoEencoder, Sorafenib, Raf kinases, Information technology, T58.5-58.64, Chemistry, QD1-999

File Description: electronic resource

Relation: https://doaj.org/toc/1758-2946

Access URL: https://doaj.org/article/01327ec5eb24459cbd7fb1c48ad25b1b

A Shadow Free Multisource Stack Sparse Autoencoder Framework for Urban Impervious Surface Mapping

Authors: Hui Lin Peifeng Ma Hongsheng Zhang et al.

Source: IGARSS 2020 - 2020 IEEE International Geoscience and Remote Sensing Symposium. :4422-4425

Subject Terms: 11. Sustainability, 0211 other engineering and technologies, 02 engineering and technology, 15. Life on land, 01 natural sciences, 0105 earth and related environmental sciences

Access URL: https://dblp.uni-trier.de/db/conf/igarss/igarss2020.html#LinZML20

Application of deep stack autoencoder network in ship weight estimation

Authors: CHEN Jian,TANG Junyao,ZHU Shengguang,ZHOU Zhaozhao

Source: Jisuanji gongcheng, Vol 45, Iss 5, Pp 315-320 (2019)

Subject Terms: airbag ship launching, deep learning, inverse gradient descent, deep stack autoencoder, layer by layer unsupervised learning, parameters fine-tuning, Computer engineering. Computer hardware, TK7885-7895, Computer software, QA76.75-76.765

File Description: electronic resource

Relation: https://www.ecice06.com/fileup/1000-3428/PDF/195315.pdf; https://doaj.org/toc/1000-3428

Access URL: https://doaj.org/article/0686b609d7de426aa1e6e2d879173cc7