BASIC NUMBER RECOGNITION EXEMPLE
This example, implemented natively in the HAIBAL library, aims to understand how to train, predict, save and load a basic model. Our idea is to help our novice users to start simply with machine learning and then hit the moon !
DATASET USED TO TRAIN THE MODEL : MNIST (MODIFIED NATIONAL INSTITUTE OF STANDARDS AND TECHNOLOGY DATABASE)
The MNIST database (Modified National Institute of Standards and Technology database) is a large database of handwritten digits that is commonly used for training various image processing systems.
The set of images in the MNIST database was created in 1998 as a combination of two of NIST’s databases: Special Database 1 and Special Database 3. Special Database 1 and Special Database 3 consist of digits written by high school students and employees of the United States Census Bureau, respectively.
THE ARCHITECTURE FOR THIS BASIC EXEMPLE
We propose two way on this exemple to solve the problem of recognition of digits numbers.
The first image is a simple 3 dense layers model and the second image is a basic convolutional way model.
The MNIST exemple will be proposed in the HAIBAL library to permit our community to use and modify it.
Software needed to run the exemple :
- LabVIEW 2020 (or latest)
- HAIBAL Deep Learning development module
