Classification of <i>Ocimum basilicum</i> Using a Convolutional Neural Network
Basil varieties were classified using a convolutional neural network (CNN) with VGG16 architecture. The developed system in this study identified and classified the variety of basil images. The system applied the contrast-limited adaptive histogram equalization (CLAHE) algorithm to the basil image i...
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| Language: | English |
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MDPI AG
2025-05-01
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| Series: | Engineering Proceedings |
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| Online Access: | https://www.mdpi.com/2673-4591/92/1/54 |
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| author | Mary Angel N. Perlas John Isaac B. Santosildes Jocelyn F. Villaverde |
| author_facet | Mary Angel N. Perlas John Isaac B. Santosildes Jocelyn F. Villaverde |
| author_sort | Mary Angel N. Perlas |
| collection | DOAJ |
| description | Basil varieties were classified using a convolutional neural network (CNN) with VGG16 architecture. The developed system in this study identified and classified the variety of basil images. The system applied the contrast-limited adaptive histogram equalization (CLAHE) algorithm to the basil image in the architecture VGG16 to extract features and classify the images. The system was tested using 50 images, and the confusion matrix showed an 82.00% accuracy. An inaccurate output was caused by the wrong positions or the size of the leaf. Of the 50 basil images, 41 were correctly classified. Two models were created in the study for epochs of eight and 10. The best model study was chosen based on accuracy. The best model showed an accuracy of 97% in training for 10 epochs. |
| format | Article |
| id | doaj-art-24045d1fdc604a9c98b2479c3aec5eeb |
| institution | Kabale University |
| issn | 2673-4591 |
| language | English |
| publishDate | 2025-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Engineering Proceedings |
| spelling | doaj-art-24045d1fdc604a9c98b2479c3aec5eeb2025-08-20T03:24:40ZengMDPI AGEngineering Proceedings2673-45912025-05-019215410.3390/engproc2025092054Classification of <i>Ocimum basilicum</i> Using a Convolutional Neural NetworkMary Angel N. Perlas0John Isaac B. Santosildes1Jocelyn F. Villaverde2School of Electrical, Electronics, and Computer Engineering, Mapúa University, Manila 1002, PhilippinesSchool of Electrical, Electronics, and Computer Engineering, Mapúa University, Manila 1002, PhilippinesSchool of Electrical, Electronics, and Computer Engineering, Mapúa University, Manila 1002, PhilippinesBasil varieties were classified using a convolutional neural network (CNN) with VGG16 architecture. The developed system in this study identified and classified the variety of basil images. The system applied the contrast-limited adaptive histogram equalization (CLAHE) algorithm to the basil image in the architecture VGG16 to extract features and classify the images. The system was tested using 50 images, and the confusion matrix showed an 82.00% accuracy. An inaccurate output was caused by the wrong positions or the size of the leaf. Of the 50 basil images, 41 were correctly classified. Two models were created in the study for epochs of eight and 10. The best model study was chosen based on accuracy. The best model showed an accuracy of 97% in training for 10 epochs.https://www.mdpi.com/2673-4591/92/1/54CNNVGG16 architecturebasilCLAHE |
| spellingShingle | Mary Angel N. Perlas John Isaac B. Santosildes Jocelyn F. Villaverde Classification of <i>Ocimum basilicum</i> Using a Convolutional Neural Network Engineering Proceedings CNN VGG16 architecture basil CLAHE |
| title | Classification of <i>Ocimum basilicum</i> Using a Convolutional Neural Network |
| title_full | Classification of <i>Ocimum basilicum</i> Using a Convolutional Neural Network |
| title_fullStr | Classification of <i>Ocimum basilicum</i> Using a Convolutional Neural Network |
| title_full_unstemmed | Classification of <i>Ocimum basilicum</i> Using a Convolutional Neural Network |
| title_short | Classification of <i>Ocimum basilicum</i> Using a Convolutional Neural Network |
| title_sort | classification of i ocimum basilicum i using a convolutional neural network |
| topic | CNN VGG16 architecture basil CLAHE |
| url | https://www.mdpi.com/2673-4591/92/1/54 |
| work_keys_str_mv | AT maryangelnperlas classificationofiocimumbasilicumiusingaconvolutionalneuralnetwork AT johnisaacbsantosildes classificationofiocimumbasilicumiusingaconvolutionalneuralnetwork AT jocelynfvillaverde classificationofiocimumbasilicumiusingaconvolutionalneuralnetwork |