Name: Deep Learning in Action: Image and Video Processing for Practical use (en Inglés)
SKU: 64393228
Price: 156.88 USD
Availability: InStock
Author: Abdussalam Elhanashi Phd; Sergio Saponara Phd
ISBN: 9780443300783

portada Deep Learning in Action: Image and Video Processing for Practical use (en Inglés)

Deep Learning in Action: Image and Video Processing for Practical use (en Inglés)

Formato

Libro Físico

Editorial

Elsevier

Autor

Abdussalam Elhanashi Phd; Sergio Saponara Phd

Idioma

Inglés

N° páginas

300

Encuadernación

Tapa Blanda

ISBN13

9780443300783

Deep Learning in Action: Image and Video Processing for Practical use (en Inglés)

Abdussalam Elhanashi Phd; Sergio Saponara Phd (Autor) · Elsevier · Tapa Blanda

Libro Nuevo Importado

Envío: 23 a 31 días háb.

$ 285.23$ 156.88

-45%

Costos de importación incluídos en el precio ✅

Libro Nuevo

Quedan 100 unidades

$ 156.88

Llega entre el 27 Oct y el 12 Nov a Quito, Pichincha. Seleccionar ubicación

Agregar a lista de deseos

Reseña del libro "Deep Learning in Action: Image and Video Processing for Practical use (en Inglés)"

Artificial intelligence technology has entered an extraordinary phase of fast development and wide application. The techniques developed in traditional AI research areas, such as computer vision and object recognition, have found many innovative applications in an array of real-world settings. The general methodological contributions from AI, such as a variety of recently developed deep learning algorithms, have also been applied to a wide spectrum of fields such as surveillance applications, real-time processing, IoT devices, and health care systems. The state-of-the-art and deep learning models have wider applicability and are highly efficient. Deep Learning in Action: Image and Video Processing for Practical Use provides a comprehensive and accessible resource for both intermediate to advanced readers seeking to harness the power of deep learning in the domains of video and image processing. The book bridges the gap between theoretical concepts and practical implementation by emphasizing lightweight approaches, enabling readers to efficiently apply deep learning techniques to real-world scenarios. It focuses on resource-efficient methods, making it particularly relevant in contexts where computational constraints are a concern.