Frontiers

Advanced AI for missing modality learning and uncertainty‑aware medical image analysis

Modern medical imaging increasingly relies on artificial intelligence to support detection, diagnosis, and prognostic ...

Bengaluru research uses AI to hunt cervical cancer risk years before diagnosis

Patent-holder’s Work Focuses On Detecting Precancerous Changes, Not Established Disease ...
Bluewin

An ugly election campaign gets even uglier - but was this the preliminary decision?

Will the failed assassination attempt help Donald Trump win the election? Many now see him at an even greater advantage.
IEEE

GrI-CNN: Granulated Deep Learning Model With Interpretable Architecture for Remote Sensing Image Classification

Abstract: Convolutional neural networks (CNNs) are highly effective deep learning architectures for remote sensing (RS) image classification. However, the interpretability of CNN architecture remains ...
GitHub

Medical Image Classification for Disease Diagnosis Using Convolutional Neural Networks

The project titled "Medical Image Classification for Disease Diagnosis Using Convolutional Neural Networks" aims to develop a robust and accurate machine learning model for the automatic ...
IEEE

Image Classification Model Based on Contrastive Learning With Dynamic Adaptive Loss

Abstract: As one of the core tasks in vision recognition, image classification is widely used in various scenarios. Most existing mainstream image classification models use the Convolutional Neural ...
Science Daily

Brain-inspired AI breakthrough: Making computers see more like humans

Researchers have developed a new artificial intelligence (AI) technique that brings machine vision closer to how the human brain processes images. Called Lp-Convolution, this method improves the ...