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eess.IV2026
Benchmarking the Alignment of Data-Quality Metrics, Human Judgment and Land-Cover Segmentation Performance for Earth Observation
Ümit Mert Çağlar, Alptekin Temizel
Volume and quality of datasets are crucial for deep learning model training, yet they are often constrained by availability and data acquisition costs. Synthetic data augmentation…
eess.IV2026
LALE: Lightweight-Transformer Architecture for Land-Cover Estimation
Ümit Mert Çağlar, Alptekin Temizel
Semantic segmentation of remote sensing imagery requires models that capture both global context and local detail under tight computational budgets. Prior work typically optimizes…
eess.IV2023
Ulcerative Colitis Mayo Endoscopic Scoring Classification with Active Learning and Generative Data Augmentation
Ümit Mert Çağlar, Alperen İnci, Oğuz Hanoğlu +2
Endoscopic imaging is commonly used to diagnose Ulcerative Colitis (UC) and classify its severity. It has been shown that deep learning based methods are effective in automated ana…