IAD Index of Academic Documents
  • Home Page
  • About
    • About Izmir Academy Association
    • About IAD Index
    • IAD Team
    • IAD Logos and Links
    • Policies
    • Contact
  • Submit A Journal
  • Submit A Conference
  • Submit Paper/Book
    • Submit a Preprint
    • Submit a Book
  • Contact
  • Turkish Journal of Science and Technology
  • Volume:18 Issue:2
  • Enhancing Strawberry Harvesting Efficiency through Yolo-v7 Object Detection Assessment

Enhancing Strawberry Harvesting Efficiency through Yolo-v7 Object Detection Assessment

Authors : Mehmet NERGİZ
Pages : 519-533
Doi:10.55525/tjst.1342555
View : 44 | Download : 84
Publication Date : 2023-09-01
Article Type : Research Paper
Abstract :Strawberry fruits which are rich in vitamin A and carotenoids offer benefits for maintaining healthy epithelial tissues and promoting maturity and growth. The intensive cultivation and swift maturation of strawberries make them susceptible to premature harvesting, leading to spoilage and financial losses for farmers. This underscores the need for an automated detection method to monitor strawberry development and accurately identify growth phases of fruits. To address this challenge, a dataset called Strawberry-DS, comprising 247 images captured in a greenhouse at the Agricultural Research Center in Giza, Egypt, is utilized in this research. The images of the dataset encompass various viewpoints, including top and angled perspectives, and illustrate six distinct growth phases: \`green\`, “red”, \`white\`, \`turning\`, \`early-turning\` and \`late-turning\`. This study employs the Yolo-v7 approach for object detection, enabling the recognition and classification of strawberries in different growth phases. The achieved [email protected] values for the growth phases are as follows: 0.37 for \`green,\` 0.335 for \`white,\` 0.505 for \`early-turning,\` 1.0 for \`turning,\` 0.337 for \`late-turning,\` and 0.804 for \`red\`. The comprehensive performance outcomes across all classes are as follows: precision at 0.792, recall at 0.575, [email protected] at 0.558, and [email protected]:.95 at 0.46. Notably, these results show the efficacy of the proposed research, both in terms of performance evaluation and visual assessment, even when dealing with distracting scenarios involving imbalanced label distributions and unclear labeling of developmental phases of the fruits. This research article yields advantages such as achieving reasonable and reliable identification of strawberries, even when operating in real-time scenarios which also leads to a decrease in expenses associated with human labor.
Keywords : Çilek, Yolo v7, Nesne tanıma, Tarım, Derin öğrenme

ORIGINAL ARTICLE URL
VIEW PAPER (PDF)

* There may have been changes in the journal, article,conference, book, preprint etc. informations. Therefore, it would be appropriate to follow the information on the official page of the source. The information here is shared for informational purposes. IAD is not responsible for incorrect or missing information.


Index of Academic Documents
İzmir Academy Association
CopyRight © 2023-2025