Machine Learning Glossary: Difference between revisions
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* Fréchet Inception Distance (FID) - a reference-based GAN evaluation metric which passes images through a pretrained network (typically Inception) and compares the distribution of intermediate features. | * Fréchet Inception Distance (FID) - a reference-based GAN evaluation metric which passes images through a pretrained network (typically Inception) and compares the distribution of intermediate features. | ||
* Fully connected network - The standard neural network model where each layer is a sequence of nodes. | * Fully connected network - The standard neural network model where each layer is a sequence of nodes. | ||
* Features | * Features - a generic term indicating the latent inputs or intermediate outputs of a neural network (2D = feature map, 3D = feature grid). | ||
==G== | ==G== | ||
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==N== | ==N== | ||
* Neurons - Individual elements in a MLP layer (perceptron + activation) which supposedly resemble brain neurons. | * Neurons - Individual elements in a MLP layer (perceptron + activation) which supposedly resemble brain neurons. | ||
* Neural Fields - A subfield of computer vision and graphics which uses neural networks to represent 3D scenes and perform tasks such as 3D reconstruction | * Neural Fields - A subfield of computer vision and graphics which uses neural networks to represent 2D/3D scenes and perform tasks such as 3D reconstruction, scene generation, and image compression. | ||
* Normalized Device Coordinates - In images, pixels are in coordinates of <math>[-1, 1]\times[-1, 1] </math>. | * Normalized Device Coordinates - In images, pixels are in coordinates of <math>[-1, 1]\times[-1, 1] </math>. | ||