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Classification of Gastrointestinal Lesions from Endoscopy Data
Accurate classification of gastrointestinal endoscopy images is important for diagnosis, yet manual assessment is subjective and subtle lesions may be overlooked. This thesis investigates endoscopic image classification using a vision transformer that was pretrained on large scale endoscopic data as
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