EurekAlert!

A novel deep learning model for medical image segmentation with convolutional neural network and transformer

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 that ...
European Medical Journal

AI Model Boosts Lung Cancer Detection Accuracy to 96%

A new hybrid AI model improves lung cancer detection on CT scans, achieving over 96% accuracy for early tumour identification ...
Frontiers

Semi-Supervised Learning with Foundation Models for Biomedical Data Analysis: Multimodality, Generative AI, and Clinical Adaptation

Biomedical data analysis has evolved rapidly from convolutional neural network-based systems toward transformer architectures and large-scale foundation ...
Semiconductor Engineering

Achieving Greater Accuracy In Real-Time Vision Processing With Transformers

Transformers, first proposed in a Google research paper in 2017, were initially designed for natural language processing (NLP) tasks. Recently, researchers applied transformers to vision applications ...
inc42

What Are Convolutional Neural Networks? Here’s All You Need to Know

What Is A Convolutional Neural Network? A Convolutional Neural Network (CNN), or CovNet, is a powerful deep learning algorithm designed to analyse visual data like images and videos. Inspired by the ...
EurekAlert!

D2-GCN: a graph convolutional network with dynamic disentanglement for node classification

Classic Graph Convolutional Networks (GCNs) often learn node representation holistically, which would ignore the distinct impacts from different neighbors when aggregating their features to update a ...
pv magazine International

PV module fault diagnosis uses convolutional neural network

Researchers in China have created a dataset of various PV faults and normalized it to accommodate different array sizes and typologies. After testing the new approach in combination with the 1D-CNN ...