Hybrid imaging and visualization : employing machine learning with Mathematica - Python / Joseph Awange, Béla Paláncz, Lajos Völgyesi

• Autore: Awange, Joseph L.
• Pubblicazione: Cham, : Springer, 2025
• Edizione: 2. ed
• Descrizione fisica: 1 testo elettronico (XXIII, 450 p. : ill.)
• Disciplina: 550(Scienze della terra e geologia - Geofisica); 526(Cartografia - Geodesia); 910(Geografia generale); 670.285(Applicazioni del computer)
• Soggetto non controllato: Computational Algorithms for Visualization; Computer Vision; Convolution Neural Networks; Data Visualization; Hybrid Symbolic-Numeric Computations; Hybrid Visualization; Hybrid imaging; Image Compression; Image Recognition; Laser Scanning; Photogrammetry; Remote sensing/photogrammetry; Restoration Images; Symbolic-Numeric Computation
• Altri autori: Paláncz, Béla Völgyesi, Lajos
• Sommario/riassunto: This second edition of the book that targets those in computer algebra and artificial intelligence introduces Black Hole algorithm that is essential for optimizing hyperparameters, an important task in machine learning where mostly, stochastic global methods are used as well as ChatGPT, a novel and in the last few years, very popular Generative AI technology. In addition, fisher discriminant, a linear discriminant that can provide an optimal separation of objects, and the conversion of time series into images thereby making it possible to employ convolution neural network to classify time series effectively are presented. (Dal sito dell'editore)
• Titolo autorizzato: Hybrid Imaging and Visualization
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: VAN00308832
• Lo trovi qui: Univ. Vanvitelli
• Localizzazioni e accesso elettronico: https://doi.org/10.1007/978-3-031-72817-4