Suchergebnisse - "Deep Stacked Autoencoder"

Customer Behavior Classification Using Deep Stacked Autoencoder with Dragonfly Optimization

Autoren: Gajendran K S Arunkumar Thangavelu

Quelle: Journal of Machine and Computing. :2230-2240

Big Data Analytics Cyber Forensic Framework Using Enhanced Sunflower Jaya Optimization- Based Deep Stacked Autoencoder

Autoren: Sabaresan V Sharon Samraj J Manjunath N

Quelle: 2025 6th International Conference for Emerging Technology (INCET). :1-7

Hybrid optimization based deep stacked autoencoder for routing and intrusion detection

Autoren: Mythili Boopathi

Quelle: Web Intelligence. 23:3-22

Schlagwörter: 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology

A Hybridized Deep Stacked Autoencoder Model for Botnet Detection

Autoren: Juliet David Shekarau Rabi Mustapha Khalid Haruna

Quelle: Kasu Journal of Computer Science. 1:1-15

Transformer Fault Diagnosis Based on Adversarial Generative Networks and Deep Stacked Autoencoder

Autoren: Lei Zhang Zhongyang Xu Chen Lu et al.

Quelle: Heliyon
Heliyon, Vol 10, Iss 9, Pp e30670-(2024)

Schlagwörter: H1-99, Transformer, Science (General), Sample expansion, Chromatographic data, 05 social sciences, 01 natural sciences, Social sciences (General), Q1-390, Adversarial neural networks, 0502 economics and business, Fault data, Research Article, 0105 earth and related environmental sciences

Zugangs-URL: https://pubmed.ncbi.nlm.nih.gov/38765093
https://doaj.org/article/cb773fe3f16d416894048132c551cb21

Deep Stacked Autoencoder-Based Long-Term Spectrum Prediction Using Real-World Data

Autoren: Guangliang Pan Qihui Wu Guoru Ding et al.

Quelle: IEEE Transactions on Cognitive Communications and Networking. 9:534-548

Emotion Recognition using Deep Stacked Autoencoder with Softmax Classifier

Autoren: M. Mohana P. Subashini

Quelle: 2023 Third International Conference on Artificial Intelligence and Smart Energy (ICAIS). :864-872

Botnet attack detection in IoT using hybrid optimisation enabled deep stacked autoencoder network

Autoren: Mahesh Babu Arrama Archana Kalidindi

Quelle: International Journal of Bio-Inspired Computation. 22:77-88

Improving Code Smell Detection Using Deep Stacked Autoencoder

Autoren: Kadem K. Rehef Ahmed S. Abbas

Quelle: Lecture Notes in Networks and Systems ISBN: 9789819633807

Deep Stacked Autoencoder-Based Automatic Emotion Recognition Using an Efficient Hybrid Local Texture Descriptor

Autoren: Shanthi Pitchaiyan Nickolas Savarimuthu

Quelle: Journal of Information Technology Research. 15:1-26

Schlagwörter: 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology

Zugangs-URL: https://www.igi-global.com/viewtitle.aspx?TitleId=282708

Robust Gesture Recognition and Classification for Visually Impaired Persons Using Growth Optimizer with Deep Stacked Autoencoder

Autoren: Mashael Maashi Mohammed Abdullah Al-Hagery Mohammed Rizwanullah et al.

Quelle: Journal of Disability Research, Vol 2, Iss 2, Pp 100-111 (2023)

Schlagwörter: Vocational rehabilitation. Employment of people with disabilities, HD7255-7256

Dateibeschreibung: electronic resource

Relation: https://www.scienceopen.com/hosted-document?doi=10.57197/JDR-2023-0029; https://doaj.org/toc/1658-9912; https://doaj.org/toc/2676-2633

Zugangs-URL: https://doaj.org/article/6203150d42e645da83f0dbf128f101c5

Feature selection and hybrid CNNF deep stacked autoencoder for botnet attack detection in IoT

Autoren: Archana Kalidindi Mahesh Babu Arrama

Quelle: Computers and Electrical Engineering. 122:109984

Positional-attention based bidirectional deep stacked AutoEncoder for aspect based sentimental analysis

Autoren: S. Anjali Devi M. Sitha Ram Pulugu Dileep et al.

Quelle: Big Data Research. 39:100505

LDSAE: LeNet Deep Stacked Autoencoder for Secure System to Mitigate the Errors of Jamming Attack in Cognitive Radio Network

Autoren: Chandrakant Athavale Chhaya K.P. Patil

Quelle: International Journal of Networking and Virtual Organisations. 31

Computer Vision with Optimal Deep Stacked Autoencoder-based Fall Activity Recognition for Disabled Persons in the IoT Environment

Autoren: Eatedal Alabdulkreem Radwa Marzouk Mesfer Alduhayyem et al.

Quelle: Journal of Disability Research, Vol 2, Iss 3, Pp 120-128 (2023)

Schlagwörter: Vocational rehabilitation. Employment of people with disabilities, HD7255-7256

Dateibeschreibung: electronic resource

Relation: https://www.scienceopen.com/hosted-document?doi=10.57197/JDR-2023-0044; https://doaj.org/toc/1658-9912; https://doaj.org/toc/2676-2633

Zugangs-URL: https://doaj.org/article/10f5d1737b124310a7c1416d302aea3e

IMS-CDA: Prediction of CircRNA-Disease Associations From the Integration of Multisource Similarity Information With Deep Stacked Autoencoder Model

Autoren: Lei Wang Zhu-Hong You Jian-Qiang Li et al.

Quelle: IEEE Transactions on Cybernetics. 51:5522-5531

Schlagwörter: 0301 basic medicine, 0303 health sciences, 03 medical and health sciences, Cluster Analysis, Computational Biology, Humans, RNA, Circular, Algorithms, 3. Good health

Zugangs-URL: https://pubmed.ncbi.nlm.nih.gov/33027025
https://pubmed.ncbi.nlm.nih.gov/33027025/
https://dblp.uni-trier.de/db/journals/tcyb/tcyb51.html#WangYLH21
https://www.ncbi.nlm.nih.gov/pubmed/33027025
https://ieeexplore.ieee.org/document/9216542/

DensePILAE: a feature reuse pseudoinverse learning algorithm for deep stacked autoencoder

Autoren: Jue Wang Ping Guo Yanjun Li

Quelle: Complex & Intelligent Systems. 8:2039-2049

Schlagwörter: 03 medical and health sciences, 0302 clinical medicine, 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology

Zugangs-URL: https://link.springer.com/content/pdf/10.1007/s40747-021-00516-5.pdf
https://link.springer.com/content/pdf/10.1007/s40747-021-00516-5.pdf
https://link.springer.com/article/10.1007/s40747-021-00516-5

An Intelligent Gestational Diabetes Diagnosis Model Using Deep Stacked Autoencoder

Autoren: B. Vijila Ravisankar S. Meganathan A. Sumathi

Quelle: Computers, Materials & Continua. 69:3109-3126

Schlagwörter: 03 medical and health sciences, 0302 clinical medicine, 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology

Zugangs-URL: https://www.techscience.com/cmc/v69n3/44131/pdf

A Secure Intrusion Detection System in Cyberphysical Systems Using a Parameter-Tuned Deep-Stacked Autoencoder

Autoren: Nojood O. Aljehane

Quelle: Computers, Materials & Continua. 68:3915-3929

Schlagwörter: 0209 industrial biotechnology, 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology

Zugangs-URL: https://www.techscience.com/cmc/v68n3/42525/pdf

Deep-stacked autoencoder for medical image classification

Autoren: J. Anitha S. Akila Agnes S. Immanuel Alex Pandian et al.

Quelle: Evolving Predictive Analytics in Healthcare: New AI techniques for real-time interventions ISBN: 9781839535116