Automatic Olive Peacock Spot Disease Recognition System Development by Using Single Shot Detector

Sinan Uğuz

doi:10.35377/saucis.03.03.755269

TR EN

Automatic Olive Peacock Spot Disease Recognition System Development by Using Single Shot Detector

Abstract

Among the artificial intelligence based studies conducted in the field of agriculture, disease recognition methods founded on deep learning are observed to become widespread. Due to the diversity and regional specificity of many plant species, studies performed in this field are not at the desired level. Olive peacock spot disease of the olive plant which grows only in certain regions in the world is a widely encountered disease particularly in Turkey. The aim of this research is to develop an olive peacock spot disease detection system using a Single Shot Detector (SSD) which is one the popular deep learning architectures to support olive farmers. This study presents a data set consisting of 1460 olive leaves samples for the detection of olive peacock spot disease. All of the images of the olive leaves which produced under controlled conditions were collected from Aegean region of Turkey during spring and summer. The data set was trained with different intersection over union (IoU) threshold values using SSD architecture. A 96 % average precision (AP) value was obtained with IoU=0.5. As IOU value goes up from 0.5, erroneously classified olive peacock spot disease symptoms growed larger as well. The AP curve becomes flat when between 0.1 and 0.5, and it decreases when greater than 0.5. This analysis showed that the IoU significantly influenced the performance of SSD based model in detection of olive peacock spot disease. In addition to, trainings were performed by employing Pytorch library and a GUI was developed for the SSD based application using PyQt5 which is one of Pyhton's libraries. Results showed that the SSD was a robust tool for recognizing the olive peacock spot disease.

Keywords

References

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Details

Primary Language

English

Subjects

Artificial Intelligence

Journal Section

Research Article

Authors

Sinan Uğuz ^*
0000-0003-4397-6196
Türkiye

Publication Date

December 30, 2020

Submission Date

June 19, 2020

Acceptance Date

September 9, 2020

Published in Issue

Year 2020 Volume: 3 Number: 3

DOI

https://doi.org/10.35377/saucis.03.03.755269

IZ

https://izlik.org/JA78PG57MM

Cite

RIS / Bibtex

APA

Uğuz, S. (2020). Automatic Olive Peacock Spot Disease Recognition System Development by Using Single Shot Detector. Sakarya University Journal of Computer and Information Sciences, 3(3), 158-168. https://doi.org/10.35377/saucis.03.03.755269

AMA

1.Uğuz S. Automatic Olive Peacock Spot Disease Recognition System Development by Using Single Shot Detector. SAUCIS. 2020;3(3):158-168. doi:10.35377/saucis.03.03.755269

Chicago

Uğuz, Sinan. 2020. “Automatic Olive Peacock Spot Disease Recognition System Development by Using Single Shot Detector”. Sakarya University Journal of Computer and Information Sciences 3 (3): 158-68. https://doi.org/10.35377/saucis.03.03.755269.

EndNote

Uğuz S (December 1, 2020) Automatic Olive Peacock Spot Disease Recognition System Development by Using Single Shot Detector. Sakarya University Journal of Computer and Information Sciences 3 3 158–168.

IEEE

[1]S. Uğuz, “Automatic Olive Peacock Spot Disease Recognition System Development by Using Single Shot Detector”, SAUCIS, vol. 3, no. 3, pp. 158–168, Dec. 2020, doi: 10.35377/saucis.03.03.755269.

ISNAD

Uğuz, Sinan. “Automatic Olive Peacock Spot Disease Recognition System Development by Using Single Shot Detector”. Sakarya University Journal of Computer and Information Sciences 3/3 (December 1, 2020): 158-168. https://doi.org/10.35377/saucis.03.03.755269.

JAMA

1.Uğuz S. Automatic Olive Peacock Spot Disease Recognition System Development by Using Single Shot Detector. SAUCIS. 2020;3:158–168.

MLA

Uğuz, Sinan. “Automatic Olive Peacock Spot Disease Recognition System Development by Using Single Shot Detector”. Sakarya University Journal of Computer and Information Sciences, vol. 3, no. 3, Dec. 2020, pp. 158-6, doi:10.35377/saucis.03.03.755269.

Vancouver

1.Sinan Uğuz. Automatic Olive Peacock Spot Disease Recognition System Development by Using Single Shot Detector. SAUCIS. 2020 Dec. 1;3(3):158-6. doi:10.35377/saucis.03.03.755269

Automatic Olive Peacock Spot Disease Recognition System Development by Using Single Shot Detector

Single Shot Detector Kullanarak Otomatik Zeytin Halkalı Leke Hastalığı Tanıma Sistemi Geliştirilmesi

Öz

Anahtar Kelimeler

Automatic Olive Peacock Spot Disease Recognition System Development by Using Single Shot Detector

Abstract

Keywords

References

Details

Primary Language

Subjects

Journal Section

Authors

Publication Date

Submission Date

Acceptance Date

Published in Issue

DOI

IZ

Cite

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