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Título de Acceso Abierto

Machine Learning in Sensors and Imaging

Resumen/Descripción – provisto por la editorial

No disponible.

Palabras clave – provistas por la editorial

star image; image denoising; reinforcement learning; maximum likelihood estimation; mixed Poisson–Gaussian likelihood; machine learning-based classification; non-uniform foundation; stochastic analysis; vehicle–pavement–foundation interaction; forest growing stem volume; coniferous plantations; variable selection; texture feature; random forest; red-edge band; on-shelf availability; semi-supervised learning; deep learning; image classification; machine learning; explainable artificial intelligence; wildfire; risk assessment; Naïve bayes; transmission-line corridors; image encryption; compressive sensing; plaintext related; chaotic system; convolutional neural network; color prior model; object detection; piston error detection; segmented telescope; BP artificial neural network; modulation transfer function; computer vision; intelligent vehicles; extrinsic camera calibration; structure from motion; convex optimization; temperature estimation; BLDC; electric machine protection; touchscreen; capacitive; display; SNR; stylus; laser cutting; quality monitoring; artificial neural network; burr formation; cut interruption; fiber laser; semi-supervised; fuzzy; noisy; real-world; plankton; marine; activity recognition; wearable sensors; imbalanced activities; sampling methods; path planning; Q-learning; neural network; YOLO algorithm; robot arm; target reaching; obstacle avoidance

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Información

Tipo de recurso:

libros

ISBN electrónico

978-3-0365-3754-2

País de edición

Suiza