Lei ling (17 Ergebnisse)

Paperback. Zustand: Good. No Jacket. Pages can have notes/highlighting. Spine may show signs of wear. ~ ThriftBooks: Read More, Spend Less.

paperback. Zustand: Very Good. Most items will be dispatched the same or the next working day. A copy that has been read, but is in excellent condition. Pages are intact and not marred by notes or highlighting. The spine remains undamaged.

paperback. Zustand: Like New. Most items will be dispatched the same or the next working day. An apparently unread copy in perfect condition. Dust cover is intact with no nicks or tears. Spine has no signs of creasing. Pages are clean and not marred by notes or folds of any kind.

HC. Zustand: Gut. Oln, Ou., gr 8?,264s., in gutem Zustand, [MSA3,5]., Deu 700g.

Zustand: Very Good. Most items will be dispatched the same or the next working day. A copy that has been read, but is in excellent condition. Pages are intact and not marred by notes or highlighting. The spine remains undamaged.

Big Book Softcover. Zustand: New. Start Up Phonics Series Edition. New 2021 Copyright In Big Book Soft Cover Format, Benchmark Education, Start Up Phonics Edition, Grade K, Unit 2: Decodable Readers Big Book, Every Story Has Characters, With Sam Likes The Farm, We See, We Sat, Full Color Illustrations, 26 Pages And Pictorial Purple And Orange Cover, A Singular Soft Cover Item; Dimensions 13.5" Wide X 11.5" High, ISBN 1532258801 (2021 Copyright) L8G. Sara Palacios, Diane Le Feyer, Rick Peterson (illustrator).…

Zustand: Very Good. Most items will be dispatched the same or the next working day. A copy that has been read, but is in excellent condition. Pages are intact and not marred by notes or highlighting. The spine remains undamaged.

Paperback. Zustand: Brand New. 260 pages. 9.50x6.25x0.50 inches. In Stock.

Zustand: Sehr gut. Zustand: Sehr gut | Seiten: 260 | Sprache: Englisch | Produktart: Bücher | With the vast development of Internet capacity and speed, as well as wide adop- tion of media technologies in people¿s daily life, a large amount of videos have been surging, and need to be efficiently processed or organized based on interest. The human visual perception system could, without difficulty, interpret and r- ognize thousands of events in videos, despite high level of video object clutters, different types of scene context, variability of motion scales, appearance changes, occlusions and object interactions. For a computer vision system, it has been be very challenging to achieve automatic video event understanding for decades. Broadly speaking, those challenges include robust detection of events under - tion clutters, event interpretation under complex scenes, multi-level semantic event inference, putting events in context and multiple cameras, event inference from object interactions, etc. In recent years, steady progress has been made towards better models for video event categorisation and recognition, e. g. , from modelling events with bag of spatial temporal features to discovering event context, from detecting events using a single camera to inferring events through a distributed camera network, and from low-level event feature extraction and description to high-level semantic event classification and recognition. Nowadays, text based video retrieval is widely used by commercial search engines. However, it is still very difficult to retrieve or categorise a specific video segment based on their content in a real multimedia system or in surveillance applications.…

Zustand: New. In.

Hardcover. Zustand: Brand New. 250 pages. 9.25x6.25x0.75 inches. In Stock.

Taschenbuch. Zustand: Neu. Intelligent Video Event Analysis and Understanding | Jianguo Zhang (u. a.) | Taschenbuch | Studies in Computational Intelligence | x | Englisch | 2016 | Springer | EAN 9783662505854 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.…

Zustand: Sehr gut. Zustand: Sehr gut | Seiten: 260 | Sprache: Englisch | Produktart: Bücher | Keine Beschreibung verfügbar.

Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - With the vast development of Internet capacity and speed, as well as wide adop- tion of media technologies in people's daily life, a large amount of videos have been surging, and need to be efficiently processed or organized based on interest. The human visual perception system could, without difficulty, interpret and r- ognize thousands of events in videos, despite high level of video object clutters, different types of scene context, variability of motion scales, appearance changes, occlusions and object interactions. For a computer vision system, it has been be very challenging to achieve automatic video event understanding for decades. Broadly speaking, those challenges include robust detection of events under - tion clutters, event interpretation under complex scenes, multi-level semantic event inference, putting events in context and multiple cameras, event inference from object interactions, etc. In recent years, steady progress has been made towards better models for video event categorisation and recognition, e. g. , from modelling events with bag of spatial temporal features to discovering event context, from detecting events using a single camera to inferring events through a distributed camera network, and from low-level event feature extraction and description to high-level semantic event classification and recognition. Nowadays, text based video retrieval is widely used by commercial search engines. However, it is still very difficult to retrieve or categorise a specific video segment based on their content in a real multimedia system or in surveillance applications.…

Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - With the vast development of Internet capacity and speed, as well as wide adop- tion of media technologies in people's daily life, a large amount of videos have been surging, and need to be efficiently processed or organized based on interest. The human visual perception system could, without difficulty, interpret and r- ognize thousands of events in videos, despite high level of video object clutters, different types of scene context, variability of motion scales, appearance changes, occlusions and object interactions. For a computer vision system, it has been be very challenging to achieve automatic video event understanding for decades. Broadly speaking, those challenges include robust detection of events under - tion clutters, event interpretation under complex scenes, multi-level semantic event inference, putting events in context and multiple cameras, event inference from object interactions, etc. In recent years, steady progress has been made towards better models for video event categorisation and recognition, e. g. , from modelling events with bag of spatial temporal features to discovering event context, from detecting events using a single camera to inferring events through a distributed camera network, and from low-level event feature extraction and description to high-level semantic event classification and recognition. Nowadays, text based video retrieval is widely used by commercial search engines. However, it is still very difficult to retrieve or categorise a specific video segment based on their content in a real multimedia system or in surveillance applications.…

Paperback. Zustand: Brand New. reprint edition. 251 pages. 9.25x6.10x0.60 inches. In Stock.

paperback. Zustand: Gut. 144 Seiten; 9787558508141.3 Gewicht in Gramm: 1.