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Sensing Technology: Current Status and Future Trends II Softcover reprint of the original 1st ed. 2014 [Mīkstie vāki]

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  • Formāts: Paperback / softback, 265 pages, height x width: 235x155 mm, weight: 4219 g, 126 Illustrations, color; 5 Illustrations, black and white; VIII, 265 p. 131 illus., 126 illus. in color., 1 Paperback / softback
  • Sērija : Smart Sensors, Measurement and Instrumentation 8
  • Izdošanas datums: 27-Aug-2016
  • Izdevniecība: Springer International Publishing AG
  • ISBN-10: 3319375385
  • ISBN-13: 9783319375380
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  • Mīkstie vāki
  • Cena: 91,53 €*
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Sensing Technology: Current Status and Future Trends II Softcover reprint of the original 1st ed. 2014Palielināt
  • Formāts: Paperback / softback, 265 pages, height x width: 235x155 mm, weight: 4219 g, 126 Illustrations, color; 5 Illustrations, black and white; VIII, 265 p. 131 illus., 126 illus. in color., 1 Paperback / softback
  • Sērija : Smart Sensors, Measurement and Instrumentation 8
  • Izdošanas datums: 27-Aug-2016
  • Izdevniecība: Springer International Publishing AG
  • ISBN-10: 3319375385
  • ISBN-13: 9783319375380
Citas grāmatas par šo tēmu:
Permanent link: https://www.kriso.lv/db/9783319375380.html
Keywords:

This book is written for academic and industry professionals working in the field of sensing, instrumentation and related fields, and is positioned to give a snapshot of the current state of the art in sensing technology, particularly from the applied perspective. The book is intended to give broad overview of the latest developments, in addition to discussing the process through which researchers go through in order to develop sensors, or related systems, which will become more widespread in the future.



This book describes the current state of the art in sensing technology, particularly from the applied perspective. Offers a broad overview of recent developments, and discusses the process through which researchers develop sensors and related systems.
From the Contents: Cochlear Implant Electrode Improvement for Stimulation and Sensing.- Machine Vision Based Techniques for Automatic Mango Fruit Sorting and Grading Based on Maturity Level and Size.-Region Adaptive, Unsharp Masking Based Lanczos-3 Interpolation for 2-D Up-Sampling: Crisp-Rule versus Fuzzy-Rule Based Approach.- Gaze-controlled Stereo Vision to Measure Position and Track a Moving Object: Machine Vision for Crane Control.