Convolutional neural network - Support vector machine based approach for classification of cyanobacteria and chlorophyta microalgae groups
Yazarlar (6)
Mesut Ersin Sonmez Karamanoğlu Mehmetbey Üniversitesi, Türkiye
Dr. Öğr. Üyesi Numan ECZACIOĞLU Karamanoğlu Mehmetbey Üniversitesi, Türkiye
Numan Emre Gumus Karamanoğlu Mehmetbey Üniversitesi, Türkiye
Muhammet Fatih Aslan Karamanoğlu Mehmetbey Üniversitesi, Türkiye
Prof. Dr. Kadir Sabanci Karamanoğlu Mehmetbey Üniversitesi, Türkiye
Baran Asikkutlu Selçuk Üniversitesi, Türkiye
| Makale Türü | Özgün Makale (SSCI, AHCI, SCI, SCI-Exp dergilerinde yayınlanan tam makale) | ||
| Dergi Adı | Algal Research (Q1) | ||
| Dergi ISSN | 2211-9264 Dergi Bilgileri (2022) | ||
| Dergi Tarandığı Indeksler | SCI-Expanded | ||
| Makale Dili | İngilizce | Basım Tarihi | 01-2022 |
| Cilt / Sayı / Sayfa | 61 / 1 / 102568–0 | DOI | 10.1016/j.algal.2021.102568 |
| Makale Linki | https://doi.org/10.1016/j.algal.2021.102568 | ||
| UAK Araştırma Alanları |
Biyoteknoloji
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| Özet |
| Microalgae are single-celled organisms that have been extensively utilized in biotechnology, pharmacology and foodstuff in recent years. The description and classification of many existing microalgae groups are carried out with classical methods in a long time and with a remarkably qualified labor force. Deep learning methods have achieved success in many fields are applied to the classification of microalga groups. In this study, Cyanobacteria and Chlorophyta microalga groups images are captured by using an inverted microscope. Data augmentation process has been carried out to increase the classification success in Convolutional Neural Network (CNN) models. The collected images are classified by employing two different methods. For the first method, classification is performed with seven different CNN models. In the second method, the Support Vector Machine (SVM) is used to increase the classification ... |
| Anahtar Kelimeler |
| Convolutional neural network | Deep learning | Image processing | Microalgae classification | Transfer learning |
Science Direct
Convolutional neural network - Support vector machine based approach for classification of cyanobacteria and chlorophyta microalgae groups
BM Sürdürülebilir Kalkınma Amaçları
| Atıf Sayıları | |
| Yöksis | 47 |
| Web of Science | 71 |
| Scopus | 90 |
| Google Scholar | 102 |