| Full text | |
| Author(s): |
Valem, Lucas Pascotti
;
Sato Kawai, Vinicius Atsushi
;
Pereira-Ferrero, Vanessa Helena
;
Guimaraes Pedronette, Daniel Carlos
;
IEEE
Total Authors: 5
|
| Document type: | Journal article |
| Source: | 2022 IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING, ICIP; v. N/A, p. 5-pg., 2022-01-01. |
| Abstract | |
Effectively measuring similarity among data samples represented as points in high-dimensional spaces remains a major challenge in retrieval, machine learning, and computer vision. In these scenarios, unsupervised manifold learning techniques grounded on rank information have been demonstrated to be a promising solution. However, various methods rely on rank correlation measures, which often depend on a proper definition of neighborhood size. On current approaches, this definition may lead to a reduction in the final desired effectiveness. In this work, a novel rank correlation measure robust to such variations is proposed for manifold learning approaches. The proposed measure is suitable for diverse scenarios and is validated on a Manifold Learning Algorithm based on Correlation Graph (CG). The experimental evaluation considered 6 datasets on general image retrieval and person Re-ID, achieving results superior to most state-of-the-art methods. (AU) | |
| FAPESP's process: | 18/15597-6 - Aplication and investigation of unsupervised learning methods in retrieval and classification tasks |
| Grantee: | Daniel Carlos Guimarães Pedronette |
| Support Opportunities: | Research Grants - Young Investigators Grants - Phase 2 |
| FAPESP's process: | 20/02183-9 - Rank-based unsupervised learning through deep learning in diverse domains |
| Grantee: | Vanessa Helena Pereira Ferrero |
| Support Opportunities: | Scholarships in Brazil - Post-Doctoral |
| FAPESP's process: | 21/07993-1 - Investigation and evaluation of rank correlation measures |
| Grantee: | Vinicius Atsushi Sato Kawai |
| Support Opportunities: | Scholarships in Brazil - Scientific Initiation |
| FAPESP's process: | 20/11366-0 - Support for computational environments and experiments execution: weakly-supervised and classification fusion methods |
| Grantee: | Lucas Pascotti Valem |
| Support Opportunities: | Scholarships in Brazil - Technical Training Program - Technical Training |