Zobrazeno 1 - 10
of 51
pro vyhledávání: '"Alexandra Albu"'
Autor:
Laura Antonelli, Federica Polverino, Alexandra Albu, Aroj Hada, Italia A. Asteriti, Francesca Degrassi, Giulia Guarguaglini, Lucia Maddalena, Mario R. Guarracino
Publikováno v:
Scientific Data, Vol 10, Iss 1, Pp 1-12 (2023)
Abstract Detecting and tracking multiple moving objects in a video is a challenging task. For living cells, the task becomes even more arduous as cells change their morphology over time, can partially overlap, and mitosis leads to new cells. Differen
Externí odkaz:
https://doaj.org/article/d311cfec11364d8dace390af0c1bb1ce
Publikováno v:
Annals of "Dunărea de Jos" University of Galaţi: Fascicle XI Shipbuilding, Vol 43, Pp 37-44 (2020)
Considering last year’s climate changes, we can expect low temperatures during winter, which can lead to the freezing of Danube river and more. This would prevent the freight traffic in Danube’s ports meaning that the riparian economy would suffe
Externí odkaz:
https://doaj.org/article/a4153a17539c45129d95151ba4a5abe8
Publikováno v:
Algorithms, Vol 15, Iss 9, p 313 (2022)
Background: Time-lapse microscopy imaging is a key approach for an increasing number of biological and biomedical studies to observe the dynamic behavior of cells over time which helps quantify important data, such as the number of cells and their si
Externí odkaz:
https://doaj.org/article/6fbb7f8c843b428cb5bd675716684fc1
Publikováno v:
Annals of "Dunărea de Jos" University of Galaţi: Fascicle XI Shipbuilding, Vol 43, Pp 37-44 (2020)
"Considering last year’s climate changes, we can expect low temperatures during winter, which can lead to the freezing of Danube river and more. This would prevent the freight traffic in Danube’s ports meaning that the riparian economy would suff
Publikováno v:
Proceedings of the Northern Lights Deep Learning Workshop; Vol. 1 (2020): Proceedings of the Northern Lights Deep Learning Workshop 2020; 6
The ability to automatically detect anomalies in brain MRI scans is of great importance in computer-aided diagnosis. Unsupervised anomaly detection methods work primarily by learning the distribution of healthy images and identifying abnormal tissues
Autor:
MIHAELA, CASSIAN DENISA1, ALEXANDRA, BOGAN1, ALEXANDRA, ALBU FLORENTINA1, LUMINIȚA, PÎRVULESCU1, NICOLETA, RABA DIANA1 dianaraba@yahoo.com
Publikováno v:
Agricultural Management / Lucrari Stiintifice Seria I, Management Agricol. 2019, Vol. 21 Issue 3, p125-130. 6p.
Autor:
Maddalena, Lucia1 (AUTHOR), Antonelli, Laura1 (AUTHOR) laura.antonelli@cnr.it, Albu, Alexandra2 (AUTHOR), Hada, Aroj2 (AUTHOR), Guarracino, Mario Rosario1,2 (AUTHOR)
Publikováno v:
Algorithms. Sep2022, Vol. 15 Issue 9, p313-313. 22p.
Autor:
Albu, Alexandra-Ioana1 (AUTHOR), Czibula, Gabriela1 (AUTHOR) gabriela.czibula@ubbcluj.ro, Mihai, Andrei1 (AUTHOR), Czibula, Istvan Gergely1 (AUTHOR), Burcea, Sorin2 (AUTHOR), Mezghani, Abdelkader3 (AUTHOR)
Publikováno v:
Remote Sensing. Aug2022, Vol. 14 Issue 16, p3890-3890. 25p.
Autor:
Strenk, Thomas Henry
Publikováno v:
Cheers; Oct2017, Vol. 28 Issue 7, p18-21, 4p
Autor:
Antonelli, Laura, Polverino, Federica, Albu, Alexandra, Hada, Aroj, Asteriti, Italia A., Degrassi, Francesca, Guarguaglini, Giulia, Maddalena, Lucia, Guarracino, Mario R.
Publikováno v:
Scientific Data; 10/4/2023, Vol. 10 Issue 1, p1-12, 12p