A research team has introduced a lightweight artificial intelligence method that accurately identifies wheat growth stages ...

Derive the Equations for the Backpropagation for Softmax and Multi-class Classification. In this video, we will see the ...

Your browser does not support the audio element. The backpropagation algorithm is the cornerstone of modern artificial intelligence. Its significance goes far beyond ...

ABSTRACT: This paper proposes a unique approach to load forecasting using a fast convergent artificial neural network (ANN) and is driven by the critical need for power system planning. The Mazoon ...

ABSTRACT: The glycemic index (GI) is a qualitative indicator of the glycemic response of a carbohydrate food. Its variability is due to the composition of the food, which in turn is related to the ...

A technical paper titled “Training neural networks with end-to-end optical backpropagation” was published by researchers at University of Oxford and Lumai Ltd. “Optics is an exciting route for the ...

Obtaining the gradient of what's known as the loss function is an essential step to establish the backpropagation algorithm developed by University of Michigan researchers to train a material. The ...

A new technical paper titled “The backpropagation algorithm implemented on spiking neuromorphic hardware” was published by University of Zurich, ETH Zurich, Los Alamos National Laboratory, Royal ...

Natural neural systems have inspired innovations in machine learning and neuromorphic circuits designed for energy-efficient data processing. However, implementing the backpropagation algorithm, a ...

Recent generations of machine learning, the methodology supporting artificial intelligence, have drawn inspiration from natural neural systems. These algorithmic approaches that mirror the complex ...