Sketch recognition        for interactive web apps

Jesús Martínez-Blanco

de.linkedin.com/in/chumo

@jmb_jesus

@chumo

Digit recognition

LeNet 1 (1993):

The first CNN with good speed and accuracy to recognise digits.

using Convolutional Neural Networks

Yann LeCun

(Bell Labs)

Soon used to read the numerical amounts on checks.

Neural Net for Handwritten Digit Recognition

http://myselph.de/neuralNet.html
Trained network from:

For web apps,

Random Forest or SVM

something fast and robust

input

feature engineering

machine learning

output

randomforest.js

svm.js

8

Andrej Karpathy

  • sample
  • normalize
  • standarize

Coordinates:

RAW

to be insensitive to the drawing speed

to be insensitive to absolute positions

Sketch recognition

feature engineering 

[
  {"label":0, "features":[4.29, 4.47, 1.80,..., 2.06]},
  {"label":1, "features":[4.85, 4.73, 3.80,..., 2.36]},
  {"label":2, "features":[4.75, 2.34, 3.12,..., 5.13]},
  {"label":3, "features":[1.40, 0.92, 4.49,..., 5.09]},
  .
  .
  .
  {"label":9, "features":[2.18, 2.04, 5.83,..., 2.96]}
]

training data set

Sketch recognition

  • Just one row per digit.
  • 50 features (coordinates or angles) per row.
  • Trains and predicts in no time in the browser.

Applications

  • Handwritten text recognition
  • Medical
  • Educational

healthy

Alzheimer

Parkinson

Clock drawing test

Technologies used

randomforest.js

svm.js
matter.js

      Sketch recognition        for interactive web apps

Jesús Martínez-Blanco

de.linkedin.com/in/chumo

@jmb_jesus

@chumo

DSR_demo

By chumo

DSR_demo

DSR demo presentation

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