Search Results - Stack autoencoder

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

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

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

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

Traffic Flow Prediction Based on Stack AutoEncoder and Long Short-Term Memory Network

Authors: Chenchen Wei Yin Tian Dongwei Xu

Source: 2020 IEEE 3rd International Conference on Automation, Electronics and Electrical Engineering (AUTEEE). :385-388

Subject Terms: 11. Sustainability, 0502 economics and business, 05 social sciences

Access URL: http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=9315723
http://xplorestaging.ieee.org/ielx7/9315291/9315531/09315723.pdf?arnumber=9315723

A new Stack Autoencoder: Neighbouring Sample Envelope Embedded Stack Autoencoder Ensemble Model

Authors: Zhou, Chuanyan Ma, Jie Li, Fan et al.

Index Terms: Computer Science - Machine Learning, Computer Science - Artificial Intelligence, text

URL: http://arxiv.org/abs/2210.14956

Continuous estimation of wrist torques with stack-autoencoder based deep neural network: A preliminary study

Authors: Yang Yu Xinjun Sheng Xiangyang Zhu et al.

Source: 2019 9th International IEEE/EMBS Conference on Neural Engineering (NER). :473-476

Subject Terms: 03 medical and health sciences, 0302 clinical medicine, 0206 medical engineering, 02 engineering and technology

Access URL: https://ieeexplore.ieee.org/document/8716941/
https://dblp.uni-trier.de/db/conf/ner/ner2019.html#YuCSZ19

Stack of discriminative autoencoders for multiclass anomaly detection in endoscopy images

Authors: Mohebbian, Mohammad Reza Wahid, Khan A. Babyn, Paul

Index Terms: Computer Science - Computer Vision and Pattern Recognition, Computer Science - Artificial Intelligence, text

URL: http://arxiv.org/abs/2103.08508

Damage assessments of composite under the environment with strong noise based on synchrosqueezing wavelet transform and stack autoencoder algorithm

Authors: Lin Sun Mingshun Jiang Lei Zhang et al.

Source: Measurement. 156:107587

Subject Terms: 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology, 0201 civil engineering

Access URL: https://jglobal.jst.go.jp/en/detail?JGLOBAL_ID=202002265278028004
https://www.sciencedirect.com/science/article/pii/S026322412030124X
https://ui.adsabs.harvard.edu/abs/2020Meas..15607587S/abstract

Rice Disease Image Recognition Based on Improved Multi-scale Stack Autoencoder

Authors: Jun Meng Lifang Fu Qiufeng Wu et al.

Source: Journal of Agricultural Science. 13:18

Subject Terms: 2. Zero hunger, 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology

Access URL: http://www.ccsenet.org/journal/index.php/jas/article/download/0/0/44369/46777
http://www.ccsenet.org/journal/index.php/jas/article/view/0/44369
https://ccsenet.org/journal/index.php/jas/article/download/0/0/44369/46777

Diesel Engine Fault Diagnosis Based on Stack Autoencoder Optimized by Harmony Search

Authors: Zhang Jinjie Mao Zhiwei Jiang Zhi-nong et al.

Source: Journal of Mechanical Engineering. 56:132

Subject Terms: 0211 other engineering and technologies, 02 engineering and technology, 0201 civil engineering

Access URL: http://www.cjmenet.com.cn/EN/10.3901/JME.2020.11.132

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

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

Source: Multimedia Tools & Applications; Dec2022, Vol. 81 Issue 29, p42163-42182, 20p

Subject Terms: ANT colonies, INTELLIGENT transportation systems, GAUSSIAN mixture models, TRAFFIC cameras, ANTS, VIDEO processing

Firmness Detection for Apples Based on Hyperspectral Imaging Technology Combined with Stack Autoencoder-Extreme Learning Machine Method

Authors: Pang Tao Chen Xiaoyan Ji Ranshi et al.

Source: Laser & Optoelectronics Progress. 56:113001

Access URL: http://www.opticsjournal.net/ViewFull0.htm?aid=OJffa38dec5fc33f0f
http://www.clp.ac.cn/EN/Article/OJ3ecdba71ff7e0d35?type=reference

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

Authors: Eftychios Protopapadakis Anastasios Doulamis Nikolaos Doulamis et al.

Source: Remote Sensing, Vol 13, Iss 3, p 371 (2021)

Subject Terms: semi-supervised learning, deep learning, stack autoencoders, building detection, remote sensing, semantic segmentation, Science

Relation: https://www.mdpi.com/2072-4292/13/3/371; https://doaj.org/toc/2072-4292; https://doaj.org/article/cd15bfe4145a455bbb00617947fb93f9

Availability: https://doi.org/10.3390/rs13030371
https://doaj.org/article/cd15bfe4145a455bbb00617947fb93f9

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)