Deep learning-based classification of colonoscopic images using an attention-enhanced ConvNeXt V2 architecture
An attention enhanced deep learning framework using ConvNeXt V2 for robust multi-class classification of colonoscopic images that demonstrates the effectiveness of modern convolutional architectures with embedded attention mechanisms in improving diagnostic performance in the analysis of colonoscopic images.