prikaz prve stranice dokumenta Deep learning methods for segmentation of images of frozen tissue sections
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doctoral thesis
Deep learning methods for segmentation of images of frozen tissue sections
Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing, 2022. urn:nbn:hr:168:827717

University of Zagreb
Faculty of Electrical Engineering and Computing
Department of Electronic Systems and Information Processing
Ruđer Bošković Institute
Division of Electronics

Cite this document

Sitnik, D. (2022). Deep learning methods for segmentation of images of frozen tissue sections (Doctoral thesis). Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing; Zagreb: Ruđer Bošković Institute. Retrieved from https://urn.nsk.hr/urn:nbn:hr:168:827717

Sitnik, Dario. "Deep learning methods for segmentation of images of frozen tissue sections." Doctoral thesis, University of Zagreb, Faculty of Electrical Engineering and Computing; Ruđer Bošković Institute, 2022. https://urn.nsk.hr/urn:nbn:hr:168:827717

Sitnik, Dario. "Deep learning methods for segmentation of images of frozen tissue sections." Doctoral thesis, University of Zagreb, Faculty of Electrical Engineering and Computing; Ruđer Bošković Institute, 2022. https://urn.nsk.hr/urn:nbn:hr:168:827717

Sitnik, D. (2022). 'Deep learning methods for segmentation of images of frozen tissue sections', Doctoral thesis, University of Zagreb, Faculty of Electrical Engineering and Computing; Ruđer Bošković Institute, accessed 22 May 2024, https://urn.nsk.hr/urn:nbn:hr:168:827717

Sitnik D. Deep learning methods for segmentation of images of frozen tissue sections [Doctoral thesis]. Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing; Zagreb: Ruđer Bošković Institute; 2022 [cited 2024 May 22] Available at: https://urn.nsk.hr/urn:nbn:hr:168:827717

D. Sitnik, "Deep learning methods for segmentation of images of frozen tissue sections", Doctoral thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb; Ruđer Bošković Institute, Zagreb, 2022. Available at: https://urn.nsk.hr/urn:nbn:hr:168:827717

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