Search Results - "Convolutional denoising autoencoder (CDAE)"

Network security situation assessment method based on ACDAE-ResBiGRU.

Authors: Li, Binyong Zhang, Jie

Source: Maintenance & Reliability / Eksploatacja i Niezawodność; 2025, Vol. 27 Issue 4, p1-19, 19p

Subject Terms: COMPUTER network security, FEATURE extraction, SITUATIONAL awareness, RISK assessment, RECURRENT neural networks, CLASSIFICATION, ARTIFICIAL neural networks, SIGNAL denoising

强噪声工况下滚动轴承的 CDAE-ResBiLSTM 故障诊断方法. (Chinese)

Alternate Title: CDAE-ResBiLSTM Fault Diagnosis Method for Rolling Bearings with Strong Noise Conditions. (English)

Authors: 马新娜 李沂阳 梁秀 et al.

Source: Journal of Zhengzhou University (Natural Science Edition); Sep2025, Vol. 57 Issue 5, p69-77, 9p

Subject Terms: LONG short-term memory, FAULT diagnosis, ROLLER bearings, AUTOENCODERS, RANDOM noise theory

Leukemia detection and classification using computer-aided diagnosis system with falcon optimization algorithm and deep learning.

Authors: Asar, Turky Omar Ragab, Mahmoud

Source: Scientific Reports; 9/18/2024, Vol. 14 Issue 1, p1-20, 20p

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

Detection of debonding defects in honeycomb sandwich composite structures using low-power ultrasound excited thermography optimized by post-processing techniques.

Authors: Zhang, Yubin Xu, Changhang Liu, Pengqian et al.

Source: Journal of Thermal Analysis & Calorimetry. Jun2025, Vol. 150 Issue 11, p8123-8145. 23p.

Subject Terms: *THERMOGRAPHY, *MANUFACTURING defects, *SIGNAL processing, *DIAGNOSTIC ultrasonic imaging, *SANDWICH construction (Materials), *IMAGE denoising, *FINITE element method, *NUMERICAL analysis

Signal‐to‐noise ratio enhancement for Raman spectra based on optimized Raman spectrometer and convolutional denoising autoencoder.

Authors: Fan, Xian‐guang Zeng, Yingjie Zhi, Yu‐Liang et al.

Source: Journal of Raman Spectroscopy; Apr2021, Vol. 52 Issue 4, p890-900, 11p

Subject Terms: RAMAN spectroscopy, SIGNAL-to-noise ratio, IMAGE denoising, RAMAN lasers, SPECTROMETERS

An Unsupervised-Learning-Based Approach for Automated Defect Inspection on Textured Surfaces.

Authors: Mei, Shuang Yang, Hua Yin, Zhouping

Source: IEEE Transactions on Instrumentation & Measurement. Jun2018, Vol. 67 Issue 6, p1266-1277. 12p.

Subject Terms: *INSPECTION & review, *MANUFACTURING defects, *GAUSSIAN measures, *RESIDUALS (Payments), *ALGORITHMS

Effective Denoising Architecture for Handling Multiple Noises.

Authors: Na Hyoun Kim Namgyu Kim

Source: Computer Systems Science & Engineering; 2023, Vol. 44 Issue 3, p2667-2682, 16p

Subject Terms: OBJECT tracking (Computer vision), IMAGE quality analysis, SIGNAL denoising, COMPUTER architecture, CONVOLUTIONAL neural networks

A novel filtering method for geodetically determined ocean surface currents using deep learning.

Authors: Gibbs, Laura Bingham, Rory J. Paiement, Adeline

Source: Environmental Data Science; 2023, Vol. 2, p1-26, 26p

Subject Terms: DEEP learning, OCEANOGRAPHY, SEA level, OCEAN currents, GENERATIVE adversarial networks

The recognition of multi-components signals based on semantic segmentation.

Authors: Hou, Changbo Fu, Dingyi Hua, Lijie et al.

Source: Wireless Networks (10220038); Jan2023, Vol. 29 Issue 1, p147-160, 14p

Subject Terms: CONVOLUTIONAL neural networks, SIGNAL-to-noise ratio

Deep Spatio-Temporal Representation and Ensemble Classification for Attention Deficit/Hyperactivity Disorder.

Authors: Liu, Shuaiqi Zhao, Ling Wang, Xu et al.

Source: IEEE Transactions on Neural Systems & Rehabilitation Engineering; 2021, Vol. 29, p1-10, 10p

Subject Terms: FUNCTIONAL magnetic resonance imaging, CONVOLUTIONAL neural networks, HYPERACTIVITY, PSYCHOLOGICAL tests, DIAGNOSIS

Predicting and optimizing the impact responses of the airbag landing system by the simulation-based deep learning model.

Authors: Shen, Xinyi Liu, Caishan

Source: Scientific Reports; 10/8/2025, Vol. 15 Issue 1, p1-20, 20p

Subject Terms: DEEP learning, CONVOLUTIONAL neural networks, MATHEMATICAL optimization, SHOCK absorbers, SAFETY, MARKOV processes, DYNAMICAL systems, FINITE element method

A Survey of EEG-Based Approaches to Classroom Attention Assessment in Education.

Authors: Wei, Lijun Yu, Yuanyu Qin, Yuping et al.

Source: Information; Oct2025, Vol. 16 Issue 10, p860, 45p

Subject Terms: ELECTROENCEPHALOGRAPHY, EDUCATIONAL evaluation, COGNITIVE ability, STUDENT engagement, SIGNAL processing, EFFECTIVE teaching, DATA integration, DEEP learning

Advancements in air quality monitoring: a systematic review of IoT-based air quality monitoring and AI technologies.

Authors: Garcia, Antony Saez, Yessica Harris, Itamar et al.

Source: Artificial Intelligence Review; Sep2025, Vol. 58 Issue 9, p1-67, 67p

Advancements and emerging trends in integrating machine learning and deep learning for SHM in mechanical and civil engineering: a comprehensive review.

Authors: Khatir, Abdelwahhab Capozucca, Roberto Khatir, Samir et al.

Source: Journal of the Brazilian Society of Mechanical Sciences & Engineering; Sep2025, Vol. 47 Issue 9, p1-34, 34p

A Hybrid Ensemble of Denoising Autoencoders and Deep Learning Models for Fetal Image Analysis.

Authors: Gornale, Shivanand Kamat, Priyanka Hiremath, Prakash et al.

Source: Cureus Journal of Computer Science; Sep2025, Vol. 2 Issue 1, p1-39, 39p

Multi-layer convolutional autoencoder for recognizing three-dimensional patterns in attention deficit hyperactivity disorder using resting-state functional magnetic resonance imaging.

Authors: Begum, Zarina Shaik, Kareemulla

Source: International Journal of Electrical & Computer Engineering (2088-8708); Aug2025, Vol. 15 Issue 4, p3965-3976, 12p

Subject Terms: ATTENTION-deficit hyperactivity disorder, FUNCTIONAL magnetic resonance imaging, SPATIO-temporal variation, DEEP learning, COGNITIVE science, CONVOLUTIONAL neural networks, MACHINE learning

Research on Bearing Fault Diagnosis Method Based on MESO-TCN.

Authors: Gao, Ruibin Zhu, Jing Wu, Yifan et al.

Source: Machines; Jul2025, Vol. 13 Issue 7, p558, 21p

Subject Terms: FAULT diagnosis, CONVOLUTIONAL neural networks, METAHEURISTIC algorithms, COST functions, MECHANICAL vibration research

An improved autoencoder for denoising acoustic emission signals in rock fracturing.

Authors: Wang, Tingting Qin, Yifan Zhao, Wanchun et al.

Source: Nondestructive Testing & Evaluation; Jun2025, Vol. 40 Issue 6, p2572-2597, 26p

Subject Terms: ACOUSTIC emission, AUTOENCODERS, STANDARD deviations, DEEP learning, SIGNAL-to-noise ratio, EMISSION control, ACOUSTIC emission testing

Inferring IGM parameters from the redshifted 21-cm power spectrum using Artificial Neural Networks.

Authors: Choudhury, Madhurima Ghara, Raghunath Zaroubi, Saleem et al.

Source: Journal of Cosmology & Astroparticle Physics; Jun2025, Vol. 2025 Issue 6, p1-32, 32p