Imagen de Portada

Deep learning method for noise localization and quality control

Fuente: Zenodo

Guardado en:

Detalles Bibliográficos
Autor principal:	Zhou, Jie
Formato:	Recurso digital
Publicado:	Zenodo 2025
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

An intelligent impulsive noise mitigation with deep learning method
por: Guo Yang, et al.
Publicado: (2024)

A comparative evaluation of CT global noise calculation methods for clinical image quality assessment
por: Charles M Weaver, et al.
Publicado: (2025)

A deep learning-based noise correction method for light-field fluorescence microscopy
por: Qu, Bohan, et al.
Publicado: (2025)

Simulation of the wind-induced secondary microseism noise
por: Zhou, Jie
Publicado: (2025)

Deep learning framework for interpretable quality control of echocardiography video
por: Liwei Du, et al.
Publicado: (2025)

Continuous-time q-learning for mean-field control with common noise, part-II: q-learning algorithms
por: Ren, Zhenjie, et al.
Publicado: (2026)

Image quality evaluation in deep‐learning‐based CT noise reduction using virtual imaging trial methods: Contrast‐dependent spatial resolution
por: Zhongxing Zhou, et al.
Publicado: (2024)

Continuous-time q-learning for mean-field control with common noise, part-I: Theoretical foundations
por: Ren, Zhenjie, et al.
Publicado: (2026)

A randomisation method for mean-field control problems with common noise
por: Denkert, Robert, et al.
Publicado: (2024)

College students’ perception of classroom noise and its consequences on learning quality
por: Emilse Aparecida Merlin Servilha
Publicado: (2014)

Deep collocation method: A framework for solving PDEs using neural networks with error control
por: Weng, Mingxing, et al.
Publicado: (2025)

Deep learning methods for protein structure prediction
por: Yiming Qin, et al.
Publicado: (2024)

Deep self-consistent learning of local volatility
por: Wang, Zhe, et al.
Publicado: (2021)

Advanced deep-reinforcement-learning methods for flow control: group-invariant and positional-encoding networks improve learning speed and quality
por: Jeon, Joongoo, et al.
Publicado: (2024)

Deep learning-based computational method for soft matter dynamics: Deep Onsager-Machlup method
por: Li, Zhihao, et al.
Publicado: (2023)

Efficient learning and optimizing non-Gaussian correlated noise in digitally controlled qubit systems
por: Dong, Wenzheng, et al.
Publicado: (2025)

Speech-preserving active noise control: a deep learning approach in reverberant environments
por: Dai, Shuning
Publicado: (2026)

Efficient learning of logical noise from syndrome data
por: Zheng, Han, et al.
Publicado: (2026)

Evaluating noises of fast-simulated boson sampling with statistical benchmark methods
por: Ji, Yang, et al.
Publicado: (2025)

Deep learning-based blind image super-resolution with iterative kernel reconstruction and noise estimation
por: Ates, Hasan F., et al.
Publicado: (2024)

Seismic noise attenuation method based on low‐rank adaptive symplectic geometry decomposition
por: Jie Fei Yang, et al.
Publicado: (2024)

Unsupervised learning based end-to-end delayless generative fixed-filter active noise control
por: Luo, Zhengding, et al.
Publicado: (2024)

The SIML method without microstructure noise
por: Akahori, Jirô, et al.
Publicado: (2023)

Quantum approaches to learning parity with noise
por: Shiu, Daniel
Publicado: (2026)

Convergence of machine learning methods for feedback control laws: averaged feedback learning scheme and data driven methods
por: Kunisch, Karl, et al.
Publicado: (2024)

Sample selection with noise rate estimation in noise learning of medical image analysis
por: Li, Maolin, et al.
Publicado: (2023)

Can shallow quantum circuits scramble local noise into global white noise?
por: Foldager, Jonathan, et al.
Publicado: (2023)

DL-Polycube: Deep learning enhanced polycube method for high-quality hexahedral mesh generation and volumetric spline construction
por: Yu, Yuxuan, et al.
Publicado: (2024)

A control variate method for threshold crossing probabilities of plastic deformation driven by transient coloured noise
por: Ip, Harry L. F., et al.
Publicado: (2025)

Deep learning classification method for boar sperm morphology analysis
por: Alexandra Keller, et al.
Publicado: (2024)

Low noise flux estimate and data quality control monitoring in EUCLID-NISP cosmological survey
por: Kubik, B., et al.
Publicado: (2025)

Transparency-controlled multiple charge transfer in superconducting junctions with local shot-noise scanning tunneling spectroscopy
por: Sato, Yudai, et al.
Publicado: (2026)

Penrose method for Kuramoto model with inertia and noise
por: Alexandrov, Artem, et al.
Publicado: (2024)

Quantum control for the Zeno effect with noise
por: Chen, Haorui, et al.
Publicado: (2024)

Comparing unsupervised learning methods for local structural identification in colloidal systems
por: Ulugöl, Alptuğ, et al.
Publicado: (2025)

Statistical quality control methods / Irving W. Burr
por: Burr, Irving W

Networked pointing system: Bearing-only target localization and pointing control
por: Li, Shiyao, et al.
Publicado: (2025)

Quantitative convergence for mean field control with common noise and degenerate idiosyncratic noise
por: Cecchin, Alekos, et al.
Publicado: (2024)

Variable-temperature attenuator calibration method for on-wafer microwave noise characterization of low-noise amplifiers
por: Ardizzi, Anthony J., et al.
Publicado: (2025)

Deep learning methods for modeling infrasound transmission loss in the middle atmosphere
por: Pichon, Alexis Le, et al.
Publicado: (2025)