BIOENGINEER

New AI Network Tackles Missing Data in Spatio-Temporal Forecasting

Researchers in Hangzhou have developed MGCRN, a graph-based recurrent neural network that maintains high forecasting accuracy ...
BIOENGINEER

Old-School Convolutional Networks Strike Back in Long-Range Time Series Forecasting

A new convolutional architecture called MRTFNet combines multi-resolution temporal embeddings with frequency-domain modeling to outperform Transformer-based models on most long-term forecasting ...
InfoQ

Meta AI’s Convolution Networks Upgrade Improves Image Classification

Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with content, and download exclusive resources. Lily Mara explains how to avoid high-risk ...
techtarget

What is a convolutional neural network (CNN)?

A convolutional neural network (CNN) is a category of machine learning model. Specifically, it is a type of deep learning algorithm that is well suited to analyzing visual data. CNNs are commonly used ...
Visual Studio Magazine

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 the MNIST digits dataset. The "Hello World" of image ...
Electronic Design

Improving Convolutional Neural Networks at the Edge

The AI revolution continuously requires new tools and methods to take full advantage of its promise, especially when dealing with imaging data beyond visible wavelengths of the electromagnetic ...
techtarget

CNN vs. GAN: How are they different?

Convolutional neural networks (CNNs) and generative adversarial networks (GANs) are examples of neural networks-- a type of deep learning algorithm modeled after how the human brain works. "GANs are ...
english.cas

Dynamic Clustering Accelerates Neural Networks on Resource-Constrained Platforms

Called Dynamic Clustering for Channel Pruning (DCCP), the method reduced the floating-point operations of ResNet-50 by 68.52% ...

Terms from Convolution Output Size to Natural Language Processing Vectorization Methods Asked in the 2nd G-Certification Mock Exam

Source: Yoshitaka Tomiyama Published: 2020-03-04 / 44 minutes / 24,000 views Scope: The second in a series of explanations ...
Semiconductor Engineering

Performance Metrics For Convolutional Neural Network Accelerators

Across the industry, there are few benchmarks that customers and potential end users can employ to evaluate an inference acceleration solution end-to-end. Early on in this space, the performance of an ...