The Lp-Convolution technique enhances AI image recognition, mimicking brain processes to improve accuracy and efficiency while reducing computational demands.

Paper Summary: U-Net: Convolutional Networks for Biomedical Image Segmentation, MICCAI 2015 Olaf Ronneberger, Philipp Fischer, and Thomas Brox [DOI] In this paper, the authors proposed a fully ...

This paper proposes an end-to-end trained fully convolutional neural network model to process 3D image volumes. Unlike previous works that processed the input volumes slice-wise or patch-wise, the ...

Accurate segmentation of medical images is essential for clinical decision-making, and deep learning techniques have shown remarkable results in this area. However, existing segmentation models ...

The complexity of convolutional neural networks (CNN), the deep learning architecture commonly used in computer vision tasks, is usually measured in the number of parameters they have. The more ...