This workshop will consider several applications based on machine learning classification and the training of artificial neural networks and deep learning.

Like all AI models based on the Transformer architecture, the large language models (LLMs) that underpin today’s coding ...

Abstract: Deep learning methods have shown promising results in various hyperspectral image (HSI) analysis tasks. Despite these advancements, existing models still struggle to accurately identify fine ...

We will create a Deep Neural Network python from scratch. We are not going to use Tensorflow or any built-in model to write the code, but it's entirely from scratch in python. We will code Deep Neural ...

The package contains a mixture of classic decoding methods and modern machine learning methods. For regression, we currently include: Wiener Filter, Wiener Cascade, Kalman Filter, Naive Bayes, Support ...

Creativity used to be the exclusive domain of humans—artists, writers, and engineers create. They receive help from sophisticated tools, which themselves were created by, and typically could be ...

Deep learning uses multi-layered neural networks that learn from data through predictions, error correction and parameter adjustments. It started with the ...

What is a neural network? A neural network, also known as an artificial neural network, is a type of machine learning that works similarly to how the human brain processes information. Instead of ...

Introduction: In the field of brain-computer interfaces (BCI), motor imagery (MI) classification is a critically important task, with the primary objective of decoding an individual's MI intentions ...

We will create a Deep Neural Network python from scratch. We are not going to use Tensorflow or any built-in model to write the code, but it's entirely from scratch in python. We will code Deep Neural ...