Git Product home page Git Product logo

gioconda's Introduction

Now--appling (or aplied) machine and deep learning in projects related to

  • OCR (license plates and similar),
  • Object detection (current method for OCR),
  • PCB inspection (siamese nets),
  • Visual kinship recognition (for a time),
  • Truck classification, and
  • Metabolomics (no more).

Skills

  • Frameworks
    • TensorFlow / Keras
    • PyTorch / PyTorchLightning (main tools)
  • ...
  • Languages
    • Python (main)
    • R (no more)
  • MLOps tooling, like DVC.

You will see here a lot of things from my dotfiles (neovim, i3, etc.) to my note-taking scripts. They are more or less updated.

Also, you will see that I have a range of interests like natural language processing, computer vision, and explainable AI. Right now I don't have anything that I find great to show you, but someday I will have them here for sure.

My blog is right at the left if you want to know more about me (WIP and currently not a priority).

gioconda's People

Contributors

pedromaf avatar vitalwarley avatar warleyvital avatar

Watchers

 avatar  avatar

Forkers

warleyvital

gioconda's Issues

Study color and produce something concrete about it

Actions to do:

  • Search for material.
  • Organize material.
  • Resume material in a good text.
  • Publish in the blog.

Key ideias to write about:

  • What is it?
  • How is it related with image processing? And with medical images?
  • More things to come...

Practical actions to do:

  • Use the key ideias from the text published to write a notebook.
  • Show images, examples, methods if possible (simple introduction).

Write a summary for a new paper: Ameling et al. (2009)

New paper (selected from Bernal et al. work, see #2):

AMELING, Stefan et al. Texture-based polyp detection in colonoscopy. In: Bildverarbeitung für die Medizin 2009. Springer, Berlin, Heidelberg, 2009. p. 346-350.

How to resume:

  • See this pdf.

Where to send it:

  • To this github repo.

Resume the selected papers from #1

Selected papers from #1:

BERNAL, Jorge; SÁNCHEZ, Javier; VILARINO, Fernando. Towards automatic polyp detection with a polyp appearance model. Pattern Recognition, v. 45, n. 9, p. 3166-3182, 2012.

How to resume:

  • See this pdf.

Where to send it:

  • To this github repo.

Study texture and produce something concrete about it

Actions to do:

  • Search for material.
  • Organize material.
  • Resume material in a good text.
  • Publish in the blog.

Key ideias to write about:

  • What is it?
  • How is it related with image processing? And with medical images?
  • More things to come...

Practical actions to do:

  • Use the key ideias from the text published to write a notebook.
  • Show images, examples, methods if possible (simple introduction).

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. 📊📈🎉

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google ❤️ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.