A multimodal neural network integrating morphology and spectral energy distribution data improves classification accuracy for ...

Recurrent Neural Network in Deep Learning. Recurrent Neural Network in Deep Learning is a model that is used for Natural ...

Researchers from the Yunnan Observatories have developed a neural network method for classifying large-scale celestial ...

Researchers at the University of Basel have developed mechanical models that can predict how effectively the different layers of a deep neural network transform data. Their results improve our ...

Researchers have developed a new photonic neural network architecture that significantly improves task accuracy by leveraging the physical properties of light. Unlike traditional designs that mimic ...

The Data Science Lab Neural Network Regression from Scratch Using C# Compared to other regression techniques, a well-tuned neural network regression system can produce the most accurate prediction ...

"The use of neural networks in the model allows us to detect this type of marker in a more flexible way, solving the problem of lighting for all phases of the detection and decoding process ...

Chainer is a fully featured neural network software that allows for easy and intuitive definition of complex neural network models. Chainer is written in Python and can be used with popular ...

Now, researchers have developed a novel neural network model that can reconstruct these reliefs as three-dimensional digital images from old photographs containing their pre-damage information.

Inspired by microscopic worms, Liquid AI’s founders developed a more adaptive, less energy-hungry kind of neural network. Now the MIT spin-off is revealing several new ultraefficient models.