Multi-year multi-crop correlation analysis in Brasov area
Abstract. Artificial Intelligence (AI) models are currently deployed in smart agriculture for various applications like crop monitoring and identification or yield estimation. AI models rely on huge amounts of data; thus, the first concern is the size and quality of labeled data for training such models. The second main concern is the explainability of the results produced by AI models. In this article, based on the 5-year data set we previously produced and published, we perform a correlation analysis in the attempt of explaining the performance of an AI model in a crop identification scenario.
Authors
- Mihai Ivanovici (ORCID: https://orcid.org/0000-0002-0803-2918)
- Ioana C. Plajer
- Luciana Majercsik
- Corneliu Florea (ORCID: https://orcid.org/0000-0001-9754-6795)
- Alexandra Băicoianu (ORCID: https://orcid.org/0000-0002-1264-3404)
- M. Ştefan (ORCID: https://orcid.org/0009-0007-2556-3642)
- Matei Debu
- Adrian Ghinea
Institutions
- Transylvania University of Brașov (RO)
- Universitatea Națională de Știință și Tehnologie Politehnica București (RO)
Publication Details
- Journal
- The international archives of the photogrammetry, remote sensing and spatial information sciences/International archives of the photogrammetry, remote sensing and spatial information sciences
- Published
- 2025-05-24
- DOI
- https://doi.org/10.5194/isprs-archives-xlviii-m-7-2025-195-2025
- Primary Topic
- Agricultural Economics and Practices
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- European Commission
- HORIZON EUROPE Framework Programme