prikaz prve stranice dokumenta Machine learning based classification of mushrooms in digital images
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master's thesis
Machine learning based classification of mushrooms in digital images
Split: University of Split, Faculty of Electrical Engineering, Mechanical Engineering and Naval Architecture, 2022. urn:nbn:hr:179:018893
Čmrlec, Luka
University of Split
Faculty of Electrical Engineering, Mechanical Engineering and Naval Architecture
Department of Electronics and Computing

Institutional repository: Repository of the Faculty of Electrical Engineering, Mechanical Engineering and Naval Architecture

Cite this document

Čmrlec, L. (2022). Machine learning based classification of mushrooms in digital images (Master's thesis). Split: University of Split, Faculty of Electrical Engineering, Mechanical Engineering and Naval Architecture. Retrieved from https://urn.nsk.hr/urn:nbn:hr:179:018893

Čmrlec, Luka. "Machine learning based classification of mushrooms in digital images." Master's thesis, University of Split, Faculty of Electrical Engineering, Mechanical Engineering and Naval Architecture, 2022. https://urn.nsk.hr/urn:nbn:hr:179:018893

Čmrlec, Luka. "Machine learning based classification of mushrooms in digital images." Master's thesis, University of Split, Faculty of Electrical Engineering, Mechanical Engineering and Naval Architecture, 2022. https://urn.nsk.hr/urn:nbn:hr:179:018893

Čmrlec, L. (2022). 'Machine learning based classification of mushrooms in digital images', Master's thesis, University of Split, Faculty of Electrical Engineering, Mechanical Engineering and Naval Architecture, accessed 11 July 2024, https://urn.nsk.hr/urn:nbn:hr:179:018893

Čmrlec L. Machine learning based classification of mushrooms in digital images [Master's thesis]. Split: University of Split, Faculty of Electrical Engineering, Mechanical Engineering and Naval Architecture; 2022 [cited 2024 July 11] Available at: https://urn.nsk.hr/urn:nbn:hr:179:018893

L. Čmrlec, "Machine learning based classification of mushrooms in digital images", Master's thesis, University of Split, Faculty of Electrical Engineering, Mechanical Engineering and Naval Architecture, Split, 2022. Available at: https://urn.nsk.hr/urn:nbn:hr:179:018893

Metadata
TitleMachine learning based classification of mushrooms in digital images
Title (croatian)Automatska klasifikacija gljiva na digitalnim slikama pomoću algoritama strojnog učenja
AuthorLuka Čmrlec
MentorMaja Braović https://orcid.org/0000-0002-3655-3534 (mentor)
GranterUniversity of Split
Faculty of Electrical Engineering, Mechanical Engineering and Naval Architecture
(Department of Electronics and Computing)
Split
Defense date and country2022-09-23, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Abstract
In this thesis, the classification of mushrooms in images was performed using machine learning algorithms. The background of neural networks is briefly discussed. Online datasets are analyzed and compared. Numerous networks are built and trained using the data acquired from online datasets. The obtained results are further improved using various methods described in the thesis. The performance of each network if rated using standard measurements.
Abstract (croatian)
U ovom radu izvedena je klasifikacija gljiva na slikama koristeći algoritme strojnog učenja. Ukratko je obrađena pozadina neuronskih mreža. Skupovi podataka pronađeni na Internetu su analizirani i uspoređeni. Brojne mreže su sagrađene i trenirane koristeći podatke sakupljene iz javno dostupnih skupova podataka. Dobiveni rezultati su unaprijeđeni raznim metodama opisanim u radu. Performanse svake od mreža su ocijenjene koristeći uobičajene mjere.
Keywords
Keywords (croatian)
Languageenglish
URN:NBNurn:nbn:hr:179:018893
Study programmeTitle: Computing
Study programme type: university
Study level: graduate
Academic / professional title: magistar/magistra inženjer/inženjerka računarstva (magistar/magistra inženjer/inženjerka računarstva)
Type of resourceText
File originBorn digital
Access conditionsAccess restricted to authenticated users
Terms of useLicence In copyright icon
Created on2023-03-24 08:36:21