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Yolov3 Tabanlı Atık Tespit Sistemleri

Year 2023, Volume: 4 Issue: 2, 160 - 176, 24.12.2023
https://doi.org/10.58769/joinssr.1390459

Abstract

Günümüzde insan sayısındaki artış, sanayi ve teknolojideki ilerlemeler, üretimin hızlanmasıyla birlikte ortaya çıkan atıkların sayısında da artışa neden olmaktadır. Bu atıkların daha kolay tespit edilmesi ve geri dönüştürülmesi ülkemizin ve dünyanın geleceği için önem arz etmektedir. Atıkların geri dönüşümü sürecinde, atıkların toplanması kadar sınıflandırılması da maliyetli enerji ve insan gücü gerektirmektedir. Atıklar temel olarak kağıt, plastik, cam ve metal olarak ayrıştırılmaktadır. Yapay zeka, derin öğrenme ve görüntü işleme gibi teknolojiler ile bu süreçlerin daha kısa ve kolay bir şekilde tamamlanması için çeşitli çalışmalar yapılmıştır. Bu çalışmada, çevrede yaygın olarak bulunan kağıt, plastik ve yiyecek-içecek atıklarından oluşan bir veri kümesi oluşturulmuştur. Bu veri kümesinde kağıt bardaklar, plastik su şişeleri ve fast food atıkları doğada farklı lokasyonlardan tespit edilerek fotoğraflanmıştır. Bu görüntüler etiketlenerek derin öğrenme algoritmalarında YoloV3 ile eğitilmiş ve test edilmiştir. Ayrıca yeni veri kümesinin performansını karşılaştırmak amacıyla literatürde kullanılan global bir veri kümesi üzerinde çalışmalar yapılmıştır. Çalışmalar sonucunda yeni oluşturulan veri kümesinin ve global veri kümesinin sınıflandırılmasında başarılı olduğu gözlemlenmiştir.

References

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A Yolov3-Based Garbage Detection Systems

Year 2023, Volume: 4 Issue: 2, 160 - 176, 24.12.2023
https://doi.org/10.58769/joinssr.1390459

Abstract

Today, the increase in the number of people, advances in industry and technology cause an increase in the number of wastes generated with the acceleration of production. It is important for the future of our country and the world that these wastes are more easily identified and recycled. In the process of recycling wastes, the classification of wastes as well as their collection requires costly energy and manpower. Wastes are basically separated into paper, plastic, glass and metal. Various studies have been carried out to complete these processes in a shorter and easier way with technologies such as artificial intelligence, deep learning and image processing. In this study, a dataset of paper, plastic and food and beverage wastes that are common in the environment was created. In this dataset, paper cups, plastic water bottles and fast food wastes were detected from different locations in nature and photographed. These images were labeled and trained and tested with YoloV3 in deep learning algorithms. In addition, in order to compare the performance of the new dataset, studies were conducted on a global dataset used in the literature. As a result of the studies, it was observed that it was successful in classifying the newly created dataset and the global dataset.

References

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There are 46 citations in total.

Details

Primary Language English
Subjects Artificial Intelligence (Other)
Journal Section Research Articles
Authors

Dilara Karaca 0000-0002-4352-4141

Süleyman Uzun 0000-0001-8246-6733

Sezgin Kaçar 0000-0002-5171-237X

Publication Date December 24, 2023
Submission Date November 13, 2023
Acceptance Date December 8, 2023
Published in Issue Year 2023 Volume: 4 Issue: 2

Cite

APA Karaca, D., Uzun, S., & Kaçar, S. (2023). A Yolov3-Based Garbage Detection Systems. Journal of Smart Systems Research, 4(2), 160-176. https://doi.org/10.58769/joinssr.1390459
AMA Karaca D, Uzun S, Kaçar S. A Yolov3-Based Garbage Detection Systems. JoinSSR. December 2023;4(2):160-176. doi:10.58769/joinssr.1390459
Chicago Karaca, Dilara, Süleyman Uzun, and Sezgin Kaçar. “A Yolov3-Based Garbage Detection Systems”. Journal of Smart Systems Research 4, no. 2 (December 2023): 160-76. https://doi.org/10.58769/joinssr.1390459.
EndNote Karaca D, Uzun S, Kaçar S (December 1, 2023) A Yolov3-Based Garbage Detection Systems. Journal of Smart Systems Research 4 2 160–176.
IEEE D. Karaca, S. Uzun, and S. Kaçar, “A Yolov3-Based Garbage Detection Systems”, JoinSSR, vol. 4, no. 2, pp. 160–176, 2023, doi: 10.58769/joinssr.1390459.
ISNAD Karaca, Dilara et al. “A Yolov3-Based Garbage Detection Systems”. Journal of Smart Systems Research 4/2 (December 2023), 160-176. https://doi.org/10.58769/joinssr.1390459.
JAMA Karaca D, Uzun S, Kaçar S. A Yolov3-Based Garbage Detection Systems. JoinSSR. 2023;4:160–176.
MLA Karaca, Dilara et al. “A Yolov3-Based Garbage Detection Systems”. Journal of Smart Systems Research, vol. 4, no. 2, 2023, pp. 160-76, doi:10.58769/joinssr.1390459.
Vancouver Karaca D, Uzun S, Kaçar S. A Yolov3-Based Garbage Detection Systems. JoinSSR. 2023;4(2):160-76.

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