8 papers
Colorectal Cancer Segmentation with Adaptive Augmentation and Multi-Resolution Ensemble Models
Ümit Mert Çağlar, Alptekin Temizel
Colorectal cancer (CRC) is the second most deadly and third most common cancer, and the leading cause of death among gastrointestinal cancers. Early diagnosis is crucial for the tr…
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…
BELDE: Building a Large-scale Earth-observation Land-cover Dataset for Europe
Ümit Mert Çağlar, Alptekin Temizel
Earth observation imagery plays a critical role in environmental monitoring, urban planning, disaster assessment, and climate analysis. While multi-spectral sensors are increasingl…
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…
Grounding Synthetic Data Generation With Vision and Language Models
Ümit Mert Çağlar, Alptekin Temizel
Deep learning models benefit from increasing data diversity and volume, motivating synthetic data augmentation to improve existing datasets. However, existing evaluation metrics fo…
Colorectal Cancer Tumor Grade Segmentation in Digital Histopathology Images: From Giga to Mini Challenge
Alper Bahcekapili, Duygu Arslan, Umut Ozdemir +16
Colorectal cancer (CRC) is the third most diagnosed cancer and the second leading cause of cancer-related death worldwide. Accurate histopathological grading of CRC is essential fo…
Exploring Challenges in Deep Learning of Single-Station Ground Motion Records
Ümit Mert Çağlar, Baris Yilmaz, Melek Türkmen +2
Contemporary deep learning models have demonstrated promising results across various applications within seismology and earthquake engineering. These models rely primarily on utili…
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…