Breaking Bicuspid

Abstract: This paper proposes a novel approach to improve the efficiency and accuracy of image classification using deep learning techniques. By integrating attention mechanisms into convolutional neural networks (CNNs), we enhance feature extraction capabilities, particularly for complex and noisy datasets. Our method achieves state-of-the-art performance on benchmark datasets such as CIFAR-10 and ImageNet. Experimental results demonstrate that the proposed model reduces computational overhead while maintaining high classification accuracy. Keywords: deep learning

convolutional neural networks

attention mechanism

image classification

computational efficiency