To tackle these challenges, we propose a novel approach utilizing adaptive neural network-based control methodology. Our method employs neural networks to approximate the low-level controller, thereby ...

Network meta-analysis (NMA) is an increasingly popular statistical method of synthesising evidence to assess the comparative benefits and harms of multiple treatments in a single analysis. Several ...

In this paper, a novel fusion method on the multimodal medical images exploiting convolutional neural network (CNN) and extreme learning ... such as computed tomography (CT), magnetic resonance ...

Centro de Física das Universidades do Minho e do Porto, Universidade do Minho, Campus de Gualtar, 4710-057 Braga, Portugal ...

The textbook meaning of an artificial neural network (ANN) is a deep learning model made up of neurons that emulate the structure of the human brain. These neurons are designed to mimic the way nerve ...

This paper proposes a theory-constrained neural network (TCNN), integrating physical significance without compromising accuracy. A theory-guided filter is applied to ensure the interpretability of ...

We had to approach this real-world problem more practically while still using network theory tools that captured enough population heterogeneity to arrive at a meaningful and useful strategy." ...

Primark has unveiled a new affordable 49-piece adaptive clothing range for men and women which includes wardrobe staples based on Primark’s bestsellers – from trench coats and tees, to jumpers and ...

This work models reinforcement-learning experiments using a recurrent neural network. It examines if the detailed credit assignment necessary for back-propagation through time can be replaced with ...

Neural Network Compression Framework (NNCF) provides a suite of post-training and training-time algorithms for optimizing inference of neural networks in OpenVINO™ with a minimal accuracy drop. NNCF ...