Classification of Terahertz Images via Caustic Lens and Transfer Learning Terahertz G r nt lerin Kostik Lens ve Transfer grenmesi Y ntemi Kullanilarak Siniflandirilmasi
8th International Artificial Intelligence and Data Processing Symposium, IDAP 2024, Malatya, Türkiye, 21 - 22 Eylül 2024, (Tam Metin Bildiri)
- Yayın Türü: Bildiri / Tam Metin Bildiri
- Doi Numarası: 10.1109/idap64064.2024.10711083
- Basıldığı Şehir: Malatya
- Basıldığı Ülke: Türkiye
- Anahtar Kelimeler: Caustic Lens, Terahertz Imaging, Transfer Learning
- Ankara Yıldırım Beyazıt Üniversitesi Adresli: Evet
Özet
Our study proposes a novel approach to reduce data processing time and improve classification accuracy in terahertz imaging. By combining a caustic lens with transfer learning, this approach enables faster and more accurate analysis of data obtained from terahertz images. Notably, the method achieved a classification accuracy of 99.38 % for five different letter shapes, demonstrating its effectiveness. This research presents a new pathway to make terahertz imaging systems faster, more accurate, and more cost-effective.