Convolutional Neural Networks (CNNs)—the most widely used AI model for image recognition—process images using ... models to ...

Our novel approach is dedicated to refining image classification using customized CNN ... This repository demonstrates a simple and effective implementation of a Convolutional Neural Network (CNN) ...

Prof. Esti Yeger-Lotem, Dr. Michael Fire, Dr. Jubran Juman, and Dr. Dima Kagan developed the algorithm to analyze these PPI networks to detect "anomalous" proteins—those that stand out due to ...

This research introduces a federated hybrid TSC method that combines image-based time series representation techniques with Convolutional Neural Networks (CNNs) in a decentralized framework.

The application of deep learning algorithms in protein structure prediction ... states and hybrid approaches integrating physical modeling. A convolutional neural network (CNN) is a type of neural ...

An image-based prediction model with convolutional neural networks (CNNs) was fine-tuned to directly identify individually aqueous solutions with different refractive indices. A new approach was ...

How do neural networks work? It's a question that can confuse novices ... results across various settings to support the CRH and PAH on tasks that include image classification and self-supervised ...