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Denoising-Dental-X-ray-Images

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software/denoising-dental-x-ray-images

Academic Project - This project afforded us a valuable opportunity to delve into the practical aspects of the Signal Processing field, with a specific emphasis on Image Processing. It involved a…

Machine-generated from the listed sources and not yet reviewed by a human.

record
Category
Software & Systems
Subcategory
unknown
License
Apache-2.0(osi)
Status
dormant
Maturity
deployed
Organization
unknown
Country
unknown
Homepage
unknown
Documentation
unknown
Tags
autoencoders · bm3d · deep-learning · denoising · dentistry · healthcare · paper · public
Regulatory
unknown
built by · 1

Top contributors by commit count, from the project’s public repository. Avatars are served by their origin, not stored here. To be removed from this list, open an issue.

similar by tags

Computed from shared tags, weighted so a rare tag counts for more than a common one. These are suggestions, not curated relationships.

  • Normative modelling using deep autoencoders: a multi-cohort study on mild cognitive impairment and Alzheimer’s disease

  • Single-Cell (Perturbation) Model Library

  • Deep-Drug-Coderautoencoders

    A tensorflow.keras generative neural network for de novo drug design, first-authored in Nature Machine Intelligence while working at AstraZeneca.

  • BiaPydenoising

    Open source Python library for building bioimage analysis pipelines

  • Paper, code, and data related to the paper "Fitness tracking reveals task-specific associations between memory, mental health, and exercise" by Jeremy R. Manning, Gina M. Notaro, Esme Chen, and…

  • dbMAPdenoising

    Deprecated in favour of TopoMetry: https://github.com/davisidarta/topometry

sources
  1. api.github.com/repos/atefbouzid/Denoising-Dental-X-ray-Images
    retrieved 2026-08-05 · via github-api

    Machine-imported from GitHub search. Last push 2024-03-22, 4 stars, license reported as Apache-2.0. Category and schematic were assigned by keyword heuristics and are unreviewed.

Not yet verified by a human. Correct this record →

machine-readable

/v1/entries/31.json→ .entries["denoising-dental-x-ray-images"]

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