Evolving Synthetic Data Generating Programs for Text Recognition Tasks - Evolving a Diverse Population of SyntheticData Generators using Genetic Programming with Novelty Search for Robust Text Recognition Models

Dissertation presented as partial requirement for obtaining the Master’s degree in Data Science and Advanced Analytics

Bibliographic Details
Main Author: Cooper, Daniel (author)
Format: masterThesis
Language:eng
Published: 2021
Subjects:
Deep Learning
Novelty Search
Genetic Programming
Synthetic Data
Algorithms
Computer Vision
Document Processing
Document Understanding
Online Access:http://hdl.handle.net/10362/114827
Country:Portugal
Oai:oai:run.unl.pt:10362/114827

Internet

http://hdl.handle.net/10362/114827

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