Search Results - improved stacked sparse denoising autoencoder*

Flatness pattern recognition based on stacked sparse denoising autoencoder and improved Osprey optimisation algorithm kernel-extreme learning machine

Authors: Zhou, Yaluo Zhang, Shaochuan Liu, Wenguang et al.

Contributors: Zhou, Yaluo Zhang, Shaochuan Liu, Wenguang et al.

Source: Ironmaking & Steelmaking: Processes, Products and Applications ; ISSN 0301-9233 1743-2812

Availability: https://doi.org/10.1177/03019233251324775
https://journals.sagepub.com/doi/pdf/10.1177/03019233251324775
https://journals.sagepub.com/doi/full-xml/10.1177/03019233251324775

M-ary Phase Position Shift Keying Demodulation Using Stacked Denoising Sparse Autoencoders

Authors: Conghui Lu Peng Chen Hua Zhong et al.

Source: Electronics, Vol 11, Iss 1233, p 1233 (2022)

Subject Terms: improved M-ary phase position shift keying (MPPSK), deep learning, autoencoders, demodulation, Electronics, TK7800-8360

Relation: https://www.mdpi.com/2079-9292/11/8/1233; https://doaj.org/toc/2079-9292; https://doaj.org/article/053078eb3108495c87da7676f4ef69bc

Availability: https://doi.org/10.3390/electronics11081233
https://doaj.org/article/053078eb3108495c87da7676f4ef69bc

Ship Shaft Frequency Extraction Based on Improved Stacked Sparse Denoising Auto-Encoder Network.

Authors: Ni, Junshuai Zhao, Mei Hu, Changqing et al.

Source: Applied Sciences (2076-3417); Sep2022, Vol. 12 Issue 18, p9076-9076, 16p

Subject Terms: DRIVE shafts, SHIP models, SHIPS, PROPELLERS

Prediction of Recurrence using a Stacked Denoising Autoencoder and Multifaceted Feature Analysis of Pretreatment MRI in Patients with Nasopharyngeal Carcinoma.

Authors: Liu Y Wang X Li J et al.

Source: Current radiopharmaceuticals [Curr Radiopharm] 2025; Vol. 18 (3), pp. 224-243.

Publication Type: Journal Article

Journal Info: Publisher: Bentham Science Publishers Country of Publication: United Arab Emirates NLM ID: 101468718 Publication Model: Print Cited Medium: Internet ISSN: 1874-4729 (Electronic) Linking ISSN: 18744710 NLM ISO Abbreviation: Curr Radiopharm Subsets: MEDLINE

MeSH Terms: Nasopharyngeal Carcinoma*/diagnostic imaging , Nasopharyngeal Carcinoma*/radiotherapy , Nasopharyngeal Carcinoma*/pathology , Magnetic Resonance Imaging*/methods , Neoplasm Recurrence, Local*/diagnostic imaging , Nasopharyngeal Neoplasms*/diagnostic imaging , Nasopharyngeal Neoplasms*/radiotherapy , Nasopharyngeal Neoplasms*/pathology, Humans ; Female ; Male ; Middle Aged ; Adult ; Retrospective Studies ; Radiotherapy, Intensity-Modulated ; Aged ; Deep Learning ; Autoencoder

Application of Artificial Intelligence Technologies as an Intervention for Promoting Healthy Eating and Nutrition in Older Adults: A Systematic Literature Review.

Authors: Kalu, Kingsley Ataguba, Grace Onifade, Oyepeju et al.

Source: Nutrients. Oct2025, Vol. 17 Issue 20, p3223. 33p.

Maximal overlap discrete wavelet transform and deep learning for robust denoising and detection of power quality disturbance.

Authors: Xiao, Fei Lu, Tianguang Wu, Mingli et al.

Source: IET Generation, Transmission & Distribution (Wiley-Blackwell); Jan2020, Vol. 14 Issue 2, p140-147, 8p

SPR: Malicious traffic detection model for CTCS-3 in railways.

Authors: Siyang Zhou Wenjiang Ji Xinhong Hei et al.

Source: High-speed Railway; Jun2025, Vol. 3 Issue 2, p105-115, 11p

Subject Terms: EXTREME learning machines, TRAFFIC monitoring, AUTOENCODERS, INDUSTRIAL controls manufacturing, MACHINE learning

A novel stacked sparse denoising autoencoder for mammography restoration to visual interpretation of breast lesion.

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

Source: Evolutionary Intelligence; Mar2021, Vol. 14 Issue 1, p133-149, 17p

Low-level structure feature extraction for image processing via stacked sparse denoising autoencoder.

Authors: Zunlin Fan Duyan Bi Linyuan He et al.

Source: Neurocomputing. Jun2017, Vol. 243, p12-20. 9p.

Subject Terms: *FEATURE extraction, *IMAGE processing, *SIGNAL denoising, *ARTIFICIAL neural networks, *DEEP learning

Software defect prediction based on stacked sparse denoising autoencoders and enhanced extreme learning machine.

Authors: Zhang, Nana Ying, Shi Zhu, Kun et al.

Source: IET Software (Wiley-Blackwell); Feb2022, Vol. 16 Issue 1, p29-47, 19p

Subject Terms: COMPUTER software quality control, COMPUTER software industry, FEATURE extraction, ELECTRONIC data processing, PARTICLE swarm optimization

Learning social representations with deep autoencoder for recommender system.

Authors: Pan, Yiteng He, Fazhi Yu, Haiping

Source: World Wide Web. Jul2020, Vol. 23 Issue 4, p2259-2279. 21p.

Subject Terms: *SOCIAL learning, *COLLECTIVE representation, *RECOMMENDER systems, *MATRIX decomposition, *SOCIAL influence, *SOCIAL interaction, *SOCIAL problems

Fault Diagnosis of Rolling Bearing Based on Multiscale Intrinsic Mode Function Permutation Entropy and a Stacked Sparse Denoising Autoencoder.

Authors: Dai, Juying Tang, Jian Shao, Faming et al.

Source: Applied Sciences (2076-3417); Jul2019, Vol. 9 Issue 13, p2743, 28p

Subject Terms: HILBERT-Huang transform, FAULT diagnosis, ENTROPY (Information theory), PERMUTATIONS, DEEP learning

Company/Entity: INTERNATIONAL Monetary Fund, SOCIETY of Automotive Engineers

Digital Image Forgery Detection Using Cyclic Symmetry Convolutional Neural Network.

Authors: S., Shashikala G. K., Ravikumar

Source: International Journal of Intelligent Engineering & Systems; 2025, Vol. 18 Issue 1, p368-379, 12p

Subject Terms: CONVOLUTIONAL neural networks, FEATURE selection, DIGITAL images, FEATURE extraction, AUTOENCODERS

Copy-Move Forgery Detection and Classification Using Improved Butterfly Optimization Algorithm-based Convolutional Neural Network.

Authors: S., Shashikala G. K., Ravikumar

Source: International Journal of Intelligent Engineering & Systems; 2024, Vol. 17 Issue 1, p869-879, 11p

Subject Terms: CONVOLUTIONAL neural networks, FORGERY, OPTIMIZATION algorithms, FEATURE extraction, FEATURE selection

An intelligent framework for skin cancer detection and classification using fusion of Squeeze-Excitation-DenseNet with Metaheuristic-driven ensemble deep learning models.

Authors: Dorathi Jayaseeli, J. D. Briskilal, J Fancy, C. et al.

Source: Scientific Reports; 3/3/2025, Vol. 15 Issue 1, p1-23, 23p

A novel optimization-driven deep learning framework for the detection of DDoS attacks.

Authors: Batchu, Raj Kumar Bikku, Thulasi Thota, Srinivasarao et al.

Source: Scientific Reports; 11/14/2024, Vol. 12 Issue 1, p1-16, 16p

Accurate prediction of drug-target interactions in Chinese and western medicine by the CWI-DTI model

Authors: Ying Li Xingyu Zhang Zhuo Chen et al.

Source: Scientific Reports, Vol 14, Iss 1, Pp 1-13 (2024)

Subject Terms: Drug-target interactions, Chinese medicine, Western medicine, Autoencoder framework, Drug databases, Medicine, Science

File Description: electronic resource

Relation: https://doaj.org/toc/2045-2322

Access URL: https://doaj.org/article/69626ab85e7547329ce14fcdec994394

Secure and Privacy-Preserving Framework for IoT-Enabled Smart Grid Environment.

Authors: Kumar, Chandan Chittora, Prakash

Source: Arabian Journal for Science & Engineering (Springer Science & Business Media B.V. ); Mar2024, Vol. 49 Issue 3, p3063-3078, 16p

Subject Terms: DEEP learning, ELECTRIC power transmission, INTELLIGENT networks, SMART meters, WIRELESS Internet, WIRELESS communications

A deep neural network with hybrid spotted hyena optimizer and grasshopper optimization algorithm for copy move forgery detection.

Authors: Gupta, Ruchi Singh, Pushpa Alam, Tanweer et al.

Source: Multimedia Tools & Applications; Jul2023, Vol. 82 Issue 16, p24547-24572, 26p

Subject Terms: OPTIMIZATION algorithms, FORGERY, GRASSHOPPERS, EVIDENCE gaps

Applications of Markov Decision Process Model and Deep Learning in Quantitative Portfolio Management during the COVID-19 Pandemic.

Authors: Yue, Han Liu, Jiapeng Zhang, Qin

Source: Systems; Oct2022, Vol. 10 Issue 5, pN.PAG-N.PAG, 20p

Subject Terms: DEEP learning, REINFORCEMENT learning, MARKOV processes, DECISION making, COVID-19 pandemic, REWARD (Psychology)