Search Results - deep stack autoencoder*

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

Fuzzy Deep Stack of Autoencoders for Dealing with Data Uncertainty

Authors: Bruno Sielly Jales Costa Jain Jinesh J

Source: 2019 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE). :1-6

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

Access URL: https://dblp.uni-trier.de/db/conf/fuzzIEEE/fuzzIEEE2019.html#CostaJ19
https://ieeexplore.ieee.org/document/8859022/

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)

Autoencoder-based confidence score for item preknowledge detection.

Authors: Pan, Yiqin

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

Subject Terms: AUTOENCODER, DEEP learning, PRIOR learning, SIMULATION methods & models, DETECTION algorithms, SIGNAL detection, TEST design

An Improved Deep Learning Model for DDoS Detection Based on Hybrid Stacked Autoencoder and Checkpoint Network.

Authors: Mousa, Amthal K. Abdullah, Mohammed Najm

Source: Future Internet. Aug2023, Vol. 15 Issue 8, p278. 16p.

Subject Terms: *Machine learning, Deep learning, Convolutional neural networks, Denial of service attacks, Botnets, Software-defined networking

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

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

Source: Entropy, Vol 25, Iss 8, p 1194 (2023)

Subject Terms: heterogeneous features, random subspace method, bearing fault diagnosis, deep stack autoencoder, lasso, Science, Astrophysics, QB460-466, Physics, QC1-999

Relation: https://www.mdpi.com/1099-4300/25/8/1194; https://doaj.org/toc/1099-4300; https://doaj.org/article/3acb3794c8c34b56ab148f36b36be24a

Availability: https://doi.org/10.3390/e25081194
https://doaj.org/article/3acb3794c8c34b56ab148f36b36be24a

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

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

SDCA: a novel stack deep convolutional autoencoder – an application on retinal image denoising.

Authors: Ghosh, Swarup Kr Biswas, Biswajit Ghosh, Anupam

Source: IET Image Processing (Wiley-Blackwell); Dec2019, Vol. 13 Issue 14, p2778-2789, 12p

Sine Cosine Based Harris Hawks Optimizer: A Hybrid Optimization Algorithm for Skin Cancer Detection Using Deep Stack Auto Encoder.

Authors: Madiwal, Shweta M. Burkpalli, Vishwanath

Source: Revue d'Intelligence Artificielle; Oct2022, Vol. 36 Issue 5, p697-708, 12p

Subject Terms: SKIN cancer, EARLY detection of cancer, FISHER discriminant analysis, MATHEMATICAL optimization, FEATURE extraction, DEEP learning

Zebra based optimal deep learning for Parkinson's disease detection using brain MRI images.

Authors: B, Santhosh Kumar P, Praveen Yadav M, Raghavendra Reddy

Source: Multimedia Tools & Applications; Aug2025, Vol. 84 Issue 26, p31395-31427, 33p

Subject Terms: PARKINSON'S disease, DEEP learning, COMPUTER-assisted image analysis (Medicine), MAGNETIC resonance imaging, OPTIMIZATION algorithms, DIMENSIONAL reduction algorithms, FEATURE extraction, CLASSIFICATION algorithms

Robust broad learning system with parametrized variational mode decomposition for schizophrenia diagnosis.

Authors: Parija, Sebamai Sahani, Mrutyunjaya Rout, Susanta Kumar

Source: Engineering Applications of Artificial Intelligence. Oct2025:Part B, Vol. 158, pN.PAG-N.PAG. 1p.

Subject Terms: *SCHIZOPHRENIA, *FEATURE extraction, *MATRIX decomposition, *COMPUTER-aided diagnosis, *NEUROPHYSIOLOGY, *DEEP learning, *MACHINE learning

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, AUTOENCODER, BLENDED learning

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

Deep Medical Image Reconstruction with Autoencoders using Deep Boltzmann Machine Training.

Authors: S., Saravanan Juliet, Sujitha

Source: EAI Endorsed Transactions on Pervasive Health & Technology; 2020, Vol. 6 Issue 24, p1-9, 9p

Subject Terms: MACHINE learning, LOGISTIC regression analysis, STAKEHOLDERS, COMPARATIVE studies, ELECTRONIC health records

Deep Adversarial Domain Adaptation Model for Bearing Fault Diagnosis.

Authors: Liu, Zhao-Hua Lu, Bi-Liang Wei, Hua-Liang et al.

Source: IEEE Transactions on Systems, Man & Cybernetics. Systems. Jul2021, Vol. 51 Issue 7, p4217-4226. 10p.

Subject Terms: *FAULT diagnosis, *DEEP learning, *ROLLER bearings, *MACHINE learning, *ROTATING machinery, *ALGORITHMS

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

EEG emotion recognition across subjects based on deep feature aggregation and multi-source domain adaptation.

Authors: Lin, Kunqiang Li, Ying He, Yiren et al.

Source: Cognitive Neurodynamics; 11/24/2025, Vol. 20 Issue 1, p1-18, 18p

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

Deep Convolutional Neural Networks Provide Motion Grading for High-Resolution Peripheral Quantitative Computed Tomography of the Scaphoid.

Authors: Benedikt, Stefan Zelger, Philipp Horling, Lukas et al.

Source: Diagnostics (2075-4418); Mar2024, Vol. 14 Issue 5, p568, 11p

Subject Terms: CONVOLUTIONAL neural networks, COMPUTED tomography, DEEP learning, ARTIFICIAL intelligence