VGG16-based Deep Learning Model for Maritime Vessel Classification Deniz Taşitlarinin Siniflandirmasi Için VGG16 Tabanli Derin Öǧrenme Modeli

Varol S., KAHRAMAN S.

2025 Innovations in Intelligent Systems and Applications Conference, ASYU 2025, Bursa, Türkiye, 10 - 12 Eylül 2025, (Tam Metin Bildiri) identifier

  • Yayın Türü: Bildiri / Tam Metin Bildiri
  • Doi Numarası: 10.1109/asyu67174.2025.11208361
  • Basıldığı Şehir: Bursa
  • Basıldığı Ülke: Türkiye
  • Anahtar Kelimeler: deep learning, Maritime surveillance, satellite image analysis
  • İstanbul Ticaret Üniversitesi Adresli: Evet

Özet

Maritime transportation serves as the backbone of global trade while being exposed to various threats such as security breaches, smuggling, illegal fishing, and environmental impacts. Therefore, it is of utmost importance that vessels are detected quickly and safely. In this study, an improved VGG16-based object detection model has been developed for the identification of maritime vessels. The model was trained and tested using the Airbus Ship Detection Challenge dataset from Kaggle. Experimental results demonstrate that the model achieves%97 accuracy in ship detection. This study is expected to provide significant contributions to maritime security and environmental monitoring systems.