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Classifier Selection Strategies based on Genetic Programming for Multimedia Recognition

Grant number: 21/02023-4
Support type:Scholarships in Brazil - Master
Effective date (Start): April 01, 2021
Effective date (End): January 31, 2023
Field of knowledge:Physical Sciences and Mathematics - Computer Science - Computing Methodologies and Techniques
Cooperation agreement: Microsoft Research
Principal Investigator:João Paulo Papa
Grantee:Rafael Junqueira Martarelli
Home Institution: Faculdade de Ciências (FC). Universidade Estadual Paulista (UNESP). Campus de Bauru. Bauru , SP, Brazil
Company:Universidade Estadual Paulista (UNESP). Campus de Rio Claro. Instituto de Geociências e Ciências Exatas (IGCE)
Associated research grant:17/25908-6 - Weakly supervised learning for compressed video analysis on retrieval and classification tasks for visual alert, AP.PITE

Abstract

This project's main objective is to implement a method for selecting classifiers through Genetic Programming (GP) multimedia recognition purposes. Learning ensemble of classifiers is not trivial since each approach may contribute differently to the final decision. Therefore, understanding each classifier's importance within the ensemble is crucial to building committees for further decision-making. The application is oriented to multimedia classification, e.g., video event or action recognition. Different approaches based on GP will also be evaluated and compared for the target application. (AU)