Universitatea Transilvania din Brasov

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Arhiva digitală instituțională ce oferă acces deschis la rezultatele cercetării științifice și la resurse pentru educație: teze de doctorat, articole științifice, baze de date, studii, rapoarte, lucrări prezentate la conferințe și alte documente relevante.

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Universitatea Transilvania din Brasov

Recent Submissions

NDVI Time Series Reconstruction Using Morphological Filtering
(Springer Science and Business Media LLC, 2025-10-13) Coliban, Radu-Mihai; Ivanovici, Mihai
Time series of Normalized Difference of Vegetation Index (NDVI) values, derived from satellite data, are useful for monitoring the vegetation status and can form a basis for more advanced analysis. However, data in these time series is affected by noise caused primarily by atmospheric conditions and acquisition errors, resulting in glitches and prompting the need for developing reconstruction techniques that can efficiently remove the noise. A multitude of approaches have been developed so far, including a variety of temporal-based methods that include filtering techniques. In this letter, a morphological filter with a non-flat structuring element is proposed for NDVI time series reconstruction. This method is applied on two time series obtained from the Copernicus Global Land Service 300 m NDVI product. The experimental results prove the effectiveness of the proposed approach in producing high-quality NDVI reconstructions, highlighted by the significantly better root mean square error (RMSE) values obtained on the considered time series in comparison with three well-established techniques.
Logit-based Superpixel Semantic Segmentation of Images for Precision Agriculture
(UNIVERSITY POLITEHNICA OF BUCHAREST SCIENTIFIC BULLETIN SERIES C-ELECTRICAL ENGINEERING AND COMPUTER SCIENCE, 2024-06-29) Florea, Corneliu; Burghiu, Alexandru; Ivanovici, Mihai
In this work we approach the problem of remote sensing image segmentation using a classical approach: the image is first segmented and, subsequently, each segment is labeled using a classifier. For segmentation, we rely on a superpixel framework and several methods are evaluated. For the classifier, again, several state-of-the-art algorithms are tested and performances are compared. The best performing method is obtained by a modified SEED superpixel algorithm with boosted trees for classification. The evaluation is carried out on the Agriculture-Vision database and the results are encouraging.
Enterprise Service Bus Solution for an Efficient Development of Geodesic Monitoring Systems
(IEEE, 2019-12) Itu, A.
Design of a service oriented architecture for a geodesic monitoring system
(IEEE, 2019-10) Itu, Alina
Optimization of a milk processing application using a service oriented architecture
(IEEE, 2019-04) Itu, Alina