For photon attenuation correction, current positron emission tomography systems combined with magnetic resonance imaging (PET/MR) imaging systems typically use methods based on MR image segmentation ...

The model is trained using gradient descent optimization. During training, the network parameters (weights and biases) are initialized randomly and updated iteratively to minimize the loss function, ...

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This paper presents a probabilistic approach for statistical modeling of the loads in distribution networks. In a distribution network, the probability density functions (pdfs) of loads at different ...

This project demonstrates the classification of satellite images using a custom Convolutional Neural Network (CNN). The model is designed to classify images from the EuroSAT dataset into ten distinct ...