OLIVE RIPENESS DETECTION SYSTEM
| dc.contributor.author | Bizhigit, Nurbol | |
| dc.contributor.author | Arslanov, Smagulkassym | |
| dc.contributor.author | Shadiyev, Akmal | |
| dc.contributor.author | Khavazmatov, Sarvar | |
| dc.contributor.author | Dunenov, Alisher | |
| dc.contributor.author | Dunenov, Alisher | |
| dc.date.accessioned | 2024-06-12T12:10:44Z | |
| dc.date.available | 2024-06-12T12:10:44Z | |
| dc.date.issued | 2024-04 | |
| dc.description.abstract | Abstract—As acute labor shortages and brain drain are being monitored in Europe, the demand for experienced specialists and labor in various fields is increasing. One such field is agriculture, specifically the olive industry. As the olive industryis one of the historically and economically significant aspects of life in the Mediterranean part of Europe, the solution of farming automatization and data-driven farming would be vital. To address this issue, we are introducing - the “Olive Ripeness Detection System.”, an automated image-processing tool designed to estimate the ripeness of olives accurately. Our system is a prerequisite system for automated means of harvesting high quality olive fruits in organic farms, which provides data-driven decisions for the farmers. | en_US |
| dc.identifier.citation | Bizhigit, N. Arslanov, S. Shadiyev, A. Khavazmatov, S. Dunenov, A. (2024). Olive Ripeness Detection System. Nazarbayev University School of Engineering and Digital Sciences. | en_US |
| dc.identifier.uri | http://nur.nu.edu.kz/handle/123456789/7843 | |
| dc.language.iso | en | en_US |
| dc.publisher | Nazarbayev University School of Engineering and Digital Sciences | en_US |
| dc.rights | CC0 1.0 Universal | * |
| dc.rights.uri | http://creativecommons.org/publicdomain/zero/1.0/ | * |
| dc.subject | Type of access: Restricted | en_US |
| dc.title | OLIVE RIPENESS DETECTION SYSTEM | en_US |
| dc.type | Bachelor's thesis | en_US |
| workflow.import.source | science |
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