HIGH-SPEED AND ACCURATE DIAGNOSIS OF GASTROINTESTINAL DISEASE: LEARNING ON ENDOSCOPY IMAGES USING LIGHTWEIGHT TRANSFORMER WITH LOCAL FEATURE ATTENTION

High-Speed and Accurate Diagnosis of Gastrointestinal Disease: Learning on Endoscopy Images Using Lightweight Transformer with Local Feature Attention

In response to the pressing need for robust disease diagnosis from gastrointestinal tract (GIT) endoscopic images, we proposed FLATer, a fast, lightweight, and highly accurate transformer-based model.FLATer consists of a residual block, a vision transformer module, and a spatial attention block, which concurrently focuses on local features and glob

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Chaotic Image Encryption Algorithm Based on Dynamic Spiral Scrambling Transform and Deoxyribonucleic Acid Encoding Operation

This article proposes a dynamic spiral scrambling algorithm, which is combined with the random pixel value filling operation, Deoxyribonucleic Acid (DNA) operation and used in image encryption.The random pixel value filling operation is viqua-f4 to generate some random values and fill them around the plain-image.These values can influence all the p

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