SCAG-Enhanced U-Net for Wheat Yellow-Rust Semantic Segmentation in Multispectral Remote Sensing

Yıl 2025, Cilt: 18 Sayı: 3, 227 - 238, 31.07.2025

İrem Ülkü

https://doi.org/10.17671/gazibtd.1648997

Öz

The wheat yellow-rust disease poses a serious risk to global wheat production, making effective detection methods essential. This study aims to enhance wheat yellow-rust detection accuracy by investigating the use of spatial-channel attention gates (scAGs) in semantic segmentation with multispectral remote sensing images. While scAGs find applications in medical image segmentation and precision agriculture, this study extends usage for wheat yellow rust detection. Integrated into the skip connections of the U-Net model, scAGs aim to refine feature extraction and improve segmentation performance. Furthermore, to address a limitation in prior work that used only one upsampling method, this study explores multiple techniques—bilinear, bicubic, nearest neighbor, and transposed convolution—optimizing performance. According to experimental results, bicubic interpolation delivers the best performance, significantly enhancing wheat yellow-rust disease detection accuracy.

Anahtar Kelimeler

Semantic segmentation , Upsampling , Spatial-channel attention , Wheat yellow-rust

SCAG ile Geliştirilmiş U-Net Kullanılarak Çok Bantlı Uzaktan Algılamada Buğday Sarı Pas Hastalığının Semantik Bölütlenmesi

Öz

Buğday sarı pas hastalığı, küresel buğday üretimi için ciddi bir tehdit oluşturmaktadır ve etkili tespit yöntemleri büyük önem taşımaktadır. Bu çalışma, çok bantlı uzaktan algılama görüntülerinde semantik bölütleme için mekânsal-kanal dikkat kapıları (SCAG'ler) kullanımını araştırarak buğday sarı pas hastalığının tespit doğruluğunu artırmayı amaçlamaktadır. SCAG'ler tıbbi görüntü bölütleme ve hassas tarım alanında kullanılmakla birlikte, bu çalışma buğday sarı pas tespiti için kullanımını genişletmektedir. U-Net modelinin atlama bağlantılarına entegre edilen SCAG'ler, özellik çıkarımını iyileştirmeyi ve bölütleme performansını artırmayı hedeflemektedir. Ayrıca, önceki çalışmalar yalnızca tek bir yukarı örnekleme yöntemi kullanırken, bu çalışmada bilineer, bikübik, en yakın komşu ve transpoz konvolüsyon gibi birden fazla teknik araştırılarak performans optimize edilmiştir. Deneysel sonuçlara göre, bikübik enterpolasyon en iyi performansı göstererek buğday sarı pas hastalığının tespit doğruluğunu önemli ölçüde artırmıştır.

Anahtar Kelimeler

Semantik bölütleme , Yukarı örnekleme , Mekânsal-kanal dikkat , Buğday sarı pas

Kaynakça

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