Digit Classification Using Signatures
Conference Year
January 2022
Abstract
The goal of classification using signatures is to improve the efficiency of neural networks and other classifiers by using less data to achieve the same or better level of accuracy. By calculating the signatures of hand drawn digits, a larger photo containing thousands of pixels can be represented by far fewer values that still allow the photo to be classified. Digits are used to showcase the benefits of classification using signatures by easily drawing a digit of your own to test the accuracy of this classification system.
Primary Faculty Mentor Name
Luis Duffaut Espinosa
Status
Undergraduate
Student College
College of Engineering and Mathematical Sciences
Program/Major
Electrical Engineering
Primary Research Category
Engineering & Physical Sciences
Digit Classification Using Signatures
The goal of classification using signatures is to improve the efficiency of neural networks and other classifiers by using less data to achieve the same or better level of accuracy. By calculating the signatures of hand drawn digits, a larger photo containing thousands of pixels can be represented by far fewer values that still allow the photo to be classified. Digits are used to showcase the benefits of classification using signatures by easily drawing a digit of your own to test the accuracy of this classification system.