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
- 614