Data acquisition applications (22 Ergebnisse)

Soft cover. Zustand: Very Good. 1 v. (various pagings) : ill. ; 21 cm. ; ISBN: 0895120496 (pbk.); 9780895120496 (pbk.) LCCN: 81-51950 ; Series: Understanding series ; pictorial stiff paper wrappers ; LC: TA1750; Dewey: 621.3815/42 ; OCLC: 8125914; Contents: Light radiation -- Light radiation sources -- Light detectors -- Optically coupled electronic systems -- Optoelectronic displays -- Applications of light-emitting diodes -- Applications of photodetectors -- Applications of photocoupled data acquisition systems -- Applications of photocoupled data transmission systems -- Applications of lasers ; slight wear to covers ; VG. Book.…

HRD. Zustand: New. New Book. Shipped from UK. Established seller since 2000.

Zustand: New. In English.

HRD. Zustand: New. New Book. Shipped from UK. Established seller since 2000.

Soft cover. Zustand: Very Good. 1st Edition. 8vo. Red soft cover, lettered in white, iv, 245pp, light toning to text-block, spine and outer joints worn, covers faded, somewhat scuffed, owner name in ink on upper front cover, small crease at upper rear corner. Very Good.

Zustand: New.

Softcover/Paperback. 2nd printing. 242 p.; figs., tabs. Good condition. Reading pages are clean and without marks. Retired library exemplar, with the usual marking. Book shows slight signs of storage and usage. No dust jacket. Still good copy. 9780960294602 Sprache: Englisch Gewicht in Gramm: 500.

Zustand: New. This is a Brand-new US Edition. This Item may be shipped from US or any other country as we have multiple locations worldwide.

Taschenbuch. Zustand: Neu. Use of GPS and CAD in Vehicle Dynamics Study | A Study of the Dynamic and In-Traffic Vehicle Behaviour Using GPS data acquisition and CAD Applications | Dinu Covaciu | Taschenbuch | Englisch | VDM Verlag Dr. Müller | EAN 9783639355895 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. …

Zustand: Used.

Taschenbuch. Zustand: Neu. Fuzzy Hierarchical Decision Modeling | Applications in Networks and Data Centers Acquisition and Design | Michael Khader | Taschenbuch | 204 S. | Englisch | 2011 | LAP LAMBERT Academic Publishing | EAN 9783847305477 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. …

Zustand: Used.

Zustand: New. In English.

Zustand: very good. Broschiert. Sofortversand aus Deutschland. Artikel wiegt maximal 500g. 242 Seiten. In englischer Sprache. Einband an Ecken/Kanten berieben. Titelblatt mit kleinem Stempel, alle anderen Seiten in gutem Zustand (ohne Stempel, Anstreichungen o.ä.).

Zustand: Sehr gut. Zustand: Sehr gut | Sprache: Englisch | Produktart: Bücher | Keine Beschreibung verfügbar.

Zustand: New. In English.

Taschenbuch. Zustand: Neu. Smart Big Data in Digital Agriculture Applications | Acquisition, Advanced Analytics, and Plant Physiology-informed Artificial Intelligence | Haoyu Niu (u. a.) | Taschenbuch | Agriculture Automation and Control | xviii | Englisch | 2025 | Springer | EAN 9783031526473 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.…

Hardcover. Zustand: Brand New. 257 pages. 9.25x6.10x0.63 inches. In Stock.

Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - In the dynamic realm of digital agriculture, the integration of big data acquisition platforms has sparked both curiosity and enthusiasm among researchers and agricultural practitioners. This book embarks on a journey to explore the intersection of artificial intelligence and agriculture, focusing on small-unmanned aerial vehicles (UAVs), unmanned ground vehicles (UGVs), edge-AI sensors and the profound impact they have on digital agriculture, particularly in the context of heterogeneous crops, such as walnuts, pomegranates, cotton, etc. For example, lightweight sensors mounted on UAVs, including multispectral and thermal infrared cameras, serve as invaluable tools for capturing high-resolution images. Their enhanced temporal and spatial resolutions, coupled with cost effectiveness and near-real-time data acquisition, position UAVs as an optimal platform for mapping and monitoring crop variability in vast expanses. This combination of data acquisition platforms and advanced analytics generates substantial datasets, necessitating a deep understanding of fractional-order thinking, which is imperative due to the inherent 'complexity' and consequent variability within the agricultural process. Much optimism is vested in the field of artificial intelligence, such as machine learning (ML) and computer vision (CV), where the efficient utilization of big data to make it 'smart' is of paramount importance in agricultural research. Central to this learning process lies the intricate relationship between plant physiology and optimization methods. The key to the learning process is the plant physiology and optimization method. Crafting an efficient optimization method raises three pivotal questions: 1.) What represents the best approach to optimization 2.) How can we achieve a more optimal optimization 3.) Is it possible to demand 'more optimal machine learning,' exemplified by deep learning, while minimizing the need for extensive labeled data for digital agriculture This book details the foundations of the plant physiology-informed machine learning (PPIML) and the principle of tail matching (POTM) framework. It is the 9th title of the 'Agriculture Automation and Control' book series published by Springer.…

Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - In the dynamic realm of digital agriculture, the integration of big data acquisition platforms has sparked both curiosity and enthusiasm among researchers and agricultural practitioners. This book embarks on a journey to explore the intersection of artificial intelligence and agriculture, focusing on small-unmanned aerial vehicles (UAVs), unmanned ground vehicles (UGVs), edge-AI sensors and the profound impact they have on digital agriculture, particularly in the context of heterogeneous crops, such as walnuts, pomegranates, cotton, etc. For example, lightweight sensors mounted on UAVs, including multispectral and thermal infrared cameras, serve as invaluable tools for capturing high-resolution images. Their enhanced temporal and spatial resolutions, coupled with cost effectiveness and near-real-time data acquisition, position UAVs as an optimal platform for mapping and monitoring crop variability in vast expanses. This combination of data acquisition platforms and advanced analytics generates substantial datasets, necessitating a deep understanding of fractional-order thinking, which is imperative due to the inherent 'complexity' and consequent variability within the agricultural process. Much optimism is vested in the field of artificial intelligence, such as machine learning (ML) and computer vision (CV), where the efficient utilization of big data to make it 'smart' is of paramount importance in agricultural research. Central to this learning process lies the intricate relationship between plant physiology and optimization methods. The key to the learning process is the plant physiology and optimization method. Crafting an efficient optimization method raises three pivotal questions: 1.) What represents the best approach to optimization 2.) How can we achieve a more optimal optimization 3.) Is it possible to demand 'more optimal machine learning,' exemplified by deep learning, while minimizing the need for extensive labeled data for digital agriculture This book details the foundations of the plant physiology-informed machine learning (PPIML) and the principle of tail matching (POTM) framework. It is the 9th title of the 'Agriculture Automation and Control' book series published by Springer.…

Zustand: New. In English.

Hardcover. Zustand: Brand New. 516 pages. 9.25x6.25x1.25 inches. In Stock.