Convolutional Neural Networks for MNIST Data Using PyTorch. Dr. James McCaffrey of Microsoft Research details the "Hello World" of image classification: a convolutional neural network (CNN) applied to ...

We developed a convolutional deep neural network-based approach named DOcking decoy selection with Voxel-based deep neural nEtwork (DOVE) for evaluating protein docking models. To evaluate a protein ...

Deep learning convolutional neural networks (CNN) for image recognition are becoming a more common method of machine learning and show promise in evaluation of complex medical imaging. In this study ...

Two Skoltech researchers have presented a highly efficient neural network model that uses data on the structure of ... Protein–Peptide Binding Site Detection Using 3D Convolutional Neural Networks.

The world of artificial intelligence (AI) is rapidly evolving, and AI is increasingly enabling applications that were previously unattainable or very difficult to implement. A subsequent article, ...

Convolutional neural networks (CNNs) are a class of deep neural networks commonly used in computer vision tasks such as image and video recognition, object detection and image segmentation.

A Convolutional Neural Network (CNN) is a form of artificial intelligence that plays a key role in the AI ecosytem due to its ability to analyze and understand visual data. The need to decipher ...

A novel neural network for preserving cultural heritage via 3D image reconstruction. ScienceDaily . Retrieved June 11, 2025 from www.sciencedaily.com / releases / 2024 / 10 / 241031131044.htm ...