| Full text | |
| Author(s): |
Marinho, Giovanna Carreira
;
Marcilio Junior, Wilson Estecio
;
Dias, Mauricio Araujo
;
Eler, Danilo Medeiros
;
Negri, Rogerio Galante
;
Casaca, Wallace
Total Authors: 6
|
| Document type: | Journal article |
| Source: | REMOTE SENSING; v. 15, n. 16, p. 24-pg., 2023-08-01. |
| Abstract | |
Dimensionality reduction is one of the most used transformations of data and plays a critical role in maintaining meaningful properties while transforming data from high- to low-dimensional spaces. Previous studies, e.g., on image analysis, comparing data from these two spaces have found that, generally, any study related to anomaly detection can achieve the same or similar results when applied to both dimensional spaces. However, there have been no studies that compare differences in these spaces related to anomaly detection strategy based on Kittler's Taxonomy (ADS-KT). This study aims to investigate the differences between both spaces when dimensionality reduction is associated with ADS-KT while analyzing a satellite image. Our methodology starts applying the pre-processing phase of the ADS-KT to create the high-dimensional space. Next, a dimensionality reduction technique generates the low-dimensional space. Then, we analyze extracted features from both spaces based on visualizations. Finally, machine-learning approaches, in accordance with the ADS-KT, produce results for both spaces. In the results section, metrics assessing transformed data present values close to zero contrasting with the high-dimensional space. Therefore, we conclude that dimensionality reduction directly impacts the application of the ADS-KT. Future work should investigate whether dimensionality reduction impacts the ADS-KT for any set of attributes. (AU) | |
| FAPESP's process: | 16/24185-8 - Anomaly detection, analysis and localization: a case study on digital static images from remote sensing applied to Cartography |
| Grantee: | Maurício Araújo Dias |
| Support Opportunities: | Scholarships abroad - Research |
| FAPESP's process: | 21/03328-3 - Development of new methodologies and machine intelligence-based technological solutions for digital image segmentation and COVID-19 pandemic response |
| Grantee: | Wallace Correa de Oliveira Casaca |
| Support Opportunities: | Regular Research Grants |
| FAPESP's process: | 20/06477-7 - Time series analysis of remote sensing images for anomaly detection |
| Grantee: | Giovanna Carreira Marinho |
| Support Opportunities: | Scholarships in Brazil - Scientific Initiation |
| FAPESP's process: | 21/01305-6 - Theoretical advances on anomaly detection and environmental monitoring systems building |
| Grantee: | Rogério Galante Negri |
| Support Opportunities: | Regular Research Grants |