ODSC - Open Data Science

SEPTEMBER 18, 2024

Convolutional neural networks (CNNs) differ from conventional, fully connected neural networks (FCNNs) because they process information in distinct ways. CNNs use a three-dimensional convolution layer and a selective type of neuron to compute critical artificial intelligence processes.

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Convolutional Neural Networks Neural Network Computer Vision Data Scientist 40

NYU Center for Data Science

SEPTEMBER 11, 2024

Shirley Ho’s research lies at the intersection of astrophysics, cosmology, and artificial intelligence. Dr. Ho’s innovative approach has led to several groundbreaking achievements: Her team at Carnegie Mellon University was the first to apply 3D convolutional neural networks in astrophysics.

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Convolutional Neural Networks Neural Network Deep Learning Data Science 54

Marktechpost

SEPTEMBER 29, 2024

In response, Google utilizes a deep neural network, CTG-net, to process the time-series data of fetal heart rate (FHR) and uterine contractions (UC) in order to predict fetal hypoxia. The CTG-net model utilizes a convolutional neural network (CNN) architecture to analyze FHR and UC signals, learning their temporal relationships.

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Deep Learning Convolutional Neural Networks AI Researcher AI Research 62

Becoming Human

JULY 23, 2024

Photo by Daniel Öberg on Unsplash Denoising CT images with Convolutional Neural Networks (CNNs) represents a significant advancement in medical imaging technology. In this article, I will discuss different approaches to CT image denoising with CNN and some traditional approaches as well.

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Convolutional Neural Networks Neural Network Deep Learning Artificial Intelligence 45

Marktechpost

SEPTEMBER 30, 2024

While the Adam optimizer has become the standard for training Transformers, stochastic gradient descent with momentum (SGD), which is highly effective for convolutional neural networks (CNNs), performs worse on Transformer models. This Magazine/Report will be released in late October/early November 2024.

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Neural Network Convolutional Neural Networks BERT Explainability 57

Flipboard

MAY 17, 2023

Best known as a robotics researcher, academic, and entrepreneur, Brooks is also an authority on AI: he directed the Computer Science and Artificial Intelligence Laboratory at MIT until 2007, and held faculty positions at Carnegie Mellon and Stanford before that. Convolutional neural networks being able to label regions of an image.

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Large Language Models Robotics Convolutional Neural Networks Neural Network 182

Becoming Human

MARCH 16, 2023

This post includes the fundamentals of graphs, combining graphs and deep learning, and an overview of Graph Neural Networks and their applications. Through the next series of this post here , I will try to make an implementation of Graph Convolutional Neural Network. So, let’s get started! What are Graphs?

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Neural Network Auto-classification Convolutional Neural Networks Auto-complete 87