Atjaunināt sīkdatņu piekrišanu

Low-Power Smart Imagers for Vision-Enabled Sensor Networks 2012 ed. [Mīkstie vāki]

  • Formāts: Paperback / softback, 156 pages, height x width: 235x155 mm, weight: 454 g, XXIV, 156 p., 1 Paperback / softback
  • Izdošanas datums: 08-May-2014
  • Izdevniecība: Springer-Verlag New York Inc.
  • ISBN-10: 1489995404
  • ISBN-13: 9781489995407
Citas grāmatas par šo tēmu:
  • Mīkstie vāki
  • Cena: 102,38 €*
  • * ši ir gala cena, t.i., netiek piemērotas nekādas papildus atlaides
  • Standarta cena: 120,44 €
  • Ietaupiet 15%
  • Grāmatu piegādes laiks ir 3-4 nedēļas, ja grāmata ir uz vietas izdevniecības noliktavā. Ja izdevējam nepieciešams publicēt jaunu tirāžu, grāmatas piegāde var aizkavēties.
  • Daudzums:
  • Ielikt grozā
  • Piegādes laiks - 4-6 nedēļas
  • Pievienot vēlmju sarakstam
  • Formāts: Paperback / softback, 156 pages, height x width: 235x155 mm, weight: 454 g, XXIV, 156 p., 1 Paperback / softback
  • Izdošanas datums: 08-May-2014
  • Izdevniecība: Springer-Verlag New York Inc.
  • ISBN-10: 1489995404
  • ISBN-13: 9781489995407
Citas grāmatas par šo tēmu:

Here is a systematic approach to developing vision system architectures that employ sensory-processing concurrency and parallel processing. It facilitates appropriate responses to a range of autonomy challenges posed by safety and surveillance applications.



This book presents a comprehensive, systematic approach to the development of vision system architectures that employ sensory-processing concurrency and parallel processing to meet the autonomy challenges posed by a variety of safety and surveillance applications. Coverage includes a thorough analysis of resistive diffusion networks embedded within an image sensor array. This analysis supports a systematic approach to the design of spatial image filters and their implementation as vision chips in CMOS technology. The book also addresses system-level considerations pertaining to the embedding of these vision chips into vision-enabled wireless sensor networks.

Describes a system-level approach for designing of vision devices and embedding them into vision-enabled, wireless sensor networks; Surveys state-of-the-art, vision-enabled WSN nodes; Includes details of specifications and challenges of vision-enabled WSNs; Explains architectures for low-energy CMOS vision chips with embedded, programmable spatial filtering capabilities; Includes considerations pertaining to the integration of vision chips into off-the-shelf WSN platforms.
Introduction.- Vision-enabled WSN Nodes: State of the Art.- Processing Primitives for Image Simplification.- VLSI Implementation of Linear Diffusion.- FLIP-Q: A QCIF Resolution Focal-plane Array for Low-power Image Processing.- Wi-FLIP: A Low-power Vision-enabled WSN Node.- Case Study: Early Detection of Forest Fires.