Optimasi YOLOv5 Berbasis Network Reduction Strategy untuk Deteksi Jenis Sel Darah

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Published Dec 16, 2023

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Ni Putu Sutramiani
Universitas Udayana

Abstract

Darah adalah kombinasi plasma dan sel yang beredar di seluruh tubuh. Komponen cair dan padat membentuk dua komponen darah. Air, protein, dan garam membentuk plasma, yang merupakan bagian cair dari darah. Sementara Trombosit, Sel Darah Merah (RBC), dan Sel Darah Putih (WBC) merupakan bagian padat. Identifikasi sel darah sangat penting karena merupakan populasi yang dapat diakses dengan mudah dan bentuk, biokimia, dan ekologinya dapat memberikan petunjuk untuk diagnosis penyakit atau kesehatan pasien secara keseluruhan. Karena banyaknya karakteristik sel dan kompleksitas data, deteksi sel yang andal dan akurat seringkali menjadi tantangan yang menantang. Kehadiran sel tertentu, seperti leukosit, dapat dideteksi dalam gambar mikroskopis. Penelitian ini mengusulkan network reduction strategy pada model YOLOv5 untuk mendeteksi jenis sel darah. Pendekatan yang diusulkan bertujuan untuk menghasilkan model YOLOv5 yang lebih optimal untuk meningkatkan kinerja model. Berdasarkan hasil eksperimen, strategi optimasi yang diusulkan dapat mendeteksi jenis sel darah dengan kinerja mencapai 94,8%.

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How to Cite
SUTRAMIANI, Ni Putu. Optimasi YOLOv5 Berbasis Network Reduction Strategy untuk Deteksi Jenis Sel Darah. Prosiding Seminar Nasional Sains dan Teknologi (Senastek), [S.l.], v. 8, n. 1, p. 279-284, dec. 2023. Available at: <https://ojs.unud.ac.id/index.php/senastek/article/view/108713>. Date accessed: 27 apr. 2024.
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Vol 8 No 1 (2023): Senastek 2023
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Articles

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