Unsupervised learning for general and multimodal multimedia retrieval

• Grant number: 20/03311-0
• Support Opportunities: Scholarships in Brazil - Master
• Start date: April 01, 2020
• End date: March 31, 2022
• Field of knowledge: Physical Sciences and Mathematics - Computer Science
• Principal Investigator: Daniel Carlos Guimarães Pedronette
• Grantee: Lucas Barbosa de Almeida
• Host Institution: Instituto de Geociências e Ciências Exatas (IGCE). Universidade Estadual Paulista (UNESP). Campus de Rio Claro. Rio Claro , SP, Brazil
• Associated research grant: 18/15597-6 - Aplication and investigation of unsupervised learning methods in retrieval and classification tasks, AP.JP2

Abstract

Rank-based Unsupervised Learning Methods have been established as a solution to increase the effectiveness of content-based searches without requiring user intervention. These methods exploit contextual relationships among images, usually encoded in the distance/similarity information of the collections. Recent related work has shown that such methods can also be applied in other retrieval scenarios, involving multimedia data, such as audio and video. The objective of this research project is to investigate the use of unsupervised learning methods for multimodal retrieval, combining several types of data, such as: audio, visual and movement. (AU)

Scientific publications

(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)

DE ALMEIDA, LUCAS BARBOSA; VALEM, LUCAS PASCOTTI; GUIMARAES PEDRONETTE, DANIEL CARLOS; IEEE. GRAPH CONVOLUTIONAL NETWORKS AND MANIFOLD RANKING FOR MULTIMODAL VIDEO RETRIEVAL. 2022 IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING, ICIP, v. N/A, p. 5-pg., 2022-01-01. (20/11366-0, 18/15597-6, 20/03311-0)

Academic Publications

(References retrieved automatically from State of São Paulo Research Institutions)

ALMEIDA, Lucas Barbosa de. Unsupervised learning for multimodal multimedia retrieval. 2022. Master's Dissertation - Universidade Estadual Paulista (Unesp). Instituto de Geociências e Ciências Exatas. Rio Claro Rio Claro.