Search Results - convolutional denoising autoencoder-convolutional neural network

Within‐project and cross‐project just‐in‐time defect prediction based on denoising autoencoder and convolutional neural network.

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

Source: IET Software (Wiley-Blackwell). Jun2020, Vol. 14 Issue 3, p185-195. 11p.

A denoising semi-supervised deep learning model for remaining useful life prediction of turbofan engine degradation.

Authors: Wang, Youming Wang, Yue

Source: Applied Intelligence; Oct2023, Vol. 53 Issue 19, p22682-22699, 18p

Subject Terms: REMAINING useful life, DEEP learning, CONVOLUTIONAL neural networks, TURBOFAN engines, SUPERVISED learning, STANDARD deviations, FEATURE extraction

Seismic Random Noise Attenuation Using a Tied-Weights Autoencoder Neural Network

Authors: Huailai Zhou Yangqin Guo Ke Guo

Source: Minerals, Vol 11, Iss 10, p 1089 (2021)

Subject Terms: autoencoder convolutional neural network, noise suppression, seismic data, tied weights, self-supervised learning, Mineralogy, QE351-399.2

Relation: https://www.mdpi.com/2075-163X/11/10/1089; https://doaj.org/toc/2075-163X; https://doaj.org/article/cbdef19ae3d04a5c823f633e54853862

Availability: https://doi.org/10.3390/min11101089
https://doaj.org/article/cbdef19ae3d04a5c823f633e54853862

Classification of massive noisy image using auto-encoders and convolutional neural network

Authors: Mahtab Ahmed Sudipta Singha Roy M. A. H. Akhand

Source: 2017 8th International Conference on Information Technology (ICIT). :971-979

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

Access URL: https://ieeexplore.ieee.org/document/8079976/
http://ieeexplore.ieee.org/document/8079976

Signal speech reconstruction and noise removal using convolutional denoising audioencoders with neural deep learning

Authors: Houda Abouzid Otman Chakkor Oscar Gabriel Reyes et al.

Source: Analog Integrated Circuits and Signal Processing. 100:501-512

Subject Terms: 03 medical and health sciences, 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology, 0305 other medical science

Access URL: https://link.springer.com/article/10.1007/s10470-019-01446-6
https://jglobal.jst.go.jp/detail?JGLOBAL_ID=201902267377708548

Hybrid deep autoencoder network based adaptive cross guided bilateral filter for motion artifacts correction and denoising from MRI.

Authors: Samuel, Shiju Ochawar, Rohini S. Rukmini, M.S.S.

Source: Imaging Science Journal. Feb2024, Vol. 72 Issue 1, p76-91. 16p.

Subject Terms: *HYBRID systems, *MOTION, *OPTIMIZATION algorithms, *MAGNETIC resonance imaging, *MEDICAL artifacts, *SIGNAL-to-noise ratio

Signal speech reconstruction and noise removal using convolutional denoising audioencoders with neural deep learning.

Authors: Abouzid, Houda Chakkor, Otman Reyes, Oscar Gabriel et al.

Source: Analog Integrated Circuits & Signal Processing; Sep2019, Vol. 100 Issue 3, p501-512, 12p

Subject Terms: DEEP learning, AUTOMATIC speech recognition, SIGNAL reconstruction

About the Application of Autoencoders For Visual Defect Detection

Authors: Rádli, Richárd Czúni, László Skala, Václav

Contributors: Rádli, Richárd Czúni, László Skala, Václav

Subject Terms: neuronová síť autoencoderu, konvoluční neuronová síť, detekce defektů, detekce anomálií bez dozoru, autoencoder neural network, convolutional neural network, defect detection, unsupervised anomaly detection

File Description: 8 s.; application/pdf

Relation: 2464–4625(CD/DVD); http://hdl.handle.net/11025/45023; https://doi.org/10.24132/CSRN.2021.3101.20

Availability: http://hdl.handle.net/11025/45023
https://doi.org/10.24132/CSRN.2021.3101.20

CCpos: WiFi Fingerprint Indoor Positioning System Based on CDAE-CNN.

Authors: Qin, Feng Zuo, Tao Wang, Xing et al.

Source: Sensors (14248220); 2/15/2021, Vol. 21 Issue 4, p1114-1114, 1p

Subject Terms: INDOOR positioning systems, CONVOLUTIONAL neural networks, K-means clustering, NANOPOSITIONING systems

BEARING FAULT DETECTION BY USING AUTOENCODER CONVOLUTIONAL NEURAL NETWORK.

Alternate Title: ВИЯВЛЕННЯ НЕСПРАВНОСТІ ПІДШИПНИКА ЗА ДОПОМОГОЮ ЗГОРТКОВОЇ НЕЙРОННОЇ МЕРЕЖІ АВТОКОДУВАЛЬНИКА. (Ukrainian)

Authors: K., Kysarin M.

Source: Radio Electronics, Computer Science, Control; 2025, Issue 2, p116-125, 10p

Subject Terms: AUTOENCODERS, CONVOLUTIONAL neural networks, MACHINE learning, OPTIMIZATION algorithms, FAULT diagnosis, MECHANICAL vibration research, NONDESTRUCTIVE testing

Enhanced Malware Classification: A Hybrid Model Utilizing Denoising Autoencoder and CNN based on visualization method.

Authors: Harika, Thippireddy Pradeepini, Gera

Source: Journal of Cybersecurity & Information Management; 2025, Vol. 16 Issue 1, p243-251, 9p

Subject Terms: CONVOLUTIONAL neural networks, MARKETING software, DEEP learning, AUTOENCODERS, BINARY codes

Multi-Source Data with Laplacian Eigenmaps and Denoising Autoencoder for Predicting Microbe-Disease Associations via Convolutional Neural Network.

Authors: Lei, Xiu-Juan Chen, Ya-Li Pan, Yi

Source: Journal of Computer Science & Technology (10009000); Mar2025, Vol. 40 Issue 2, p588-604, 17p

Subject Terms: CONVOLUTIONAL neural networks, AUTOENCODERS, GRAPH algorithms, NERVOUS system, BIPOLAR disorder

Practical Convolutional Neural Networks : Implement Advanced Deep Learning Models Using Python

Authors: Mohit Sewak Md. Rezaul Karim Pradeep Pujari

Resource Type: eBook.

Subjects: Computer vision, Neural networks (Computer science), Machine learning, Python (Computer program language)

Categories: COMPUTERS / Image Processing, COMPUTERS / Artificial Intelligence / General, COMPUTERS / Information Technology

Deep Learning Algorithms for Human Activity Recognition in Manual Material Handling Tasks.

Authors: Bassani, Giulia Avizzano, Carlo Alberto Filippeschi, Alessandro

Source: Sensors (14248220); Nov2025, Vol. 25 Issue 21, p6705, 20p

Subject Terms: HUMAN activity recognition, MATERIALS handling, CONVOLUTIONAL neural networks, DEEP learning, RECOGNITION (Psychology), WEARABLE technology, INDUSTRIAL safety, LONG short-term memory

Denoising and Baseline Correction Methods for Raman Spectroscopy Based on Convolutional Autoencoder: A Unified Solution.

Authors: Han, Ming Dang, Yu Han, Jianda

Source: Sensors (14248220); May2024, Vol. 24 Issue 10, p3161, 15p

Subject Terms: RAMAN spectroscopy, CONVOLUTIONAL neural networks, IMAGE denoising, NOISE control, SIGNAL processing

Image dehazing using autoencoder convolutional neural network.

Authors: Singh, Richa Dubey, Ashwani Kumar Kapoor, Rajiv

Source: International Journal of Systems Assurance Engineering & Management; Dec2022, Vol. 13 Issue 6, p3002-3016, 15p

AutoCRW: Learning based robust watermarking for smart city applications.

Authors: Amrit, Preetam Singh, Amit Kumar

Source: Software: Practice & Experience; Oct2024, Vol. 54 Issue 10, p1957-1971, 15p

Subject Terms: CONVOLUTIONAL neural networks, NATURAL language processing, IMAGE recognition (Computer vision), INTELLECTUAL property theft, COPYRIGHT

Enhancing Sensor-Based Human Physical Activity Recognition Using Deep Neural Networks.

Authors: Sassi Hidri, Minyar Hidri, Adel Alsaif, Suleiman Ali et al.

Source: Journal of Sensor & Actuator Networks; Apr2025, Vol. 14 Issue 2, p42, 22p

Subject Terms: ARTIFICIAL neural networks, LONG short-term memory, HUMAN activity recognition, RECURRENT neural networks, CONVOLUTIONAL neural networks, DEEP learning

Comparison of noise reduction performance of denoising autoencoders with CNN and LSTM.

Authors: Pichika, S. V. V. S. Narayana Chaitanya, Malireddy Yuva Rajasekharan, Sabareesh Geetha et al.

Source: AIP Conference Proceedings; 2023, Vol. 2715 Issue 1, p1-12, 12p

Subject Terms: CONVOLUTIONAL neural networks, SIGNAL-to-noise ratio, STANDARD deviations, ACOUSTIC vibrations, NOISE control, SIGNAL denoising

Design and development of an indoor navigation system using denoising autoencoder based convolutional neural network for visually impaired people.

Authors: Akilandeswari, J. Jothi, G. Naveenkumar, A. et al.

Source: Multimedia Tools & Applications; Jan2022, Vol. 81 Issue 3, p3483-3514, 32p

Subject Terms: CONVOLUTIONAL neural networks, PEOPLE with visual disabilities, RADIAL basis functions, DEEP learning, VISION disorders, RAILROAD stations