Ikeuchi katsushi (124 risultati)

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Da: Better World Books, Mishawaka, U.S.A.Better World Books
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Condizione: Good. Former library copy. Pages intact with minimal writing/highlighting. The binding may be loose and creased. Dust jackets/supplements are not included. Includes library markings. Stock photo provided. Product includes identifying sticker. Better World Books: Buy Books. Do Good.

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Da: Midtown Scholar Bookstore, Harrisburg, U.S.A.Midtown Scholar Bookstore
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EUR 39,74
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Hardcover. Condizione: Good. some shelfwear/edgewear but still NICE! - may have remainder mark or previous owner's name Standard-sized.

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Da: Hay-on-Wye Booksellers, Hay-on-Wye, Regno UnitoHay-on-Wye Booksellers
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EUR 17,95
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Condizione: Very Good.

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Da: Kloof Booksellers & Scientia Verlag, Amsterdam, Paesi BassiKloof Booksellers & Scientia Verlag
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EUR 20,95
EUR 30,00 spedizioneSpedito da Paesi Bassi a U.S.A.Quantità: 1 disponibili
Condizione: very good. New York & Oxford : Oxford University Press, 1997, Hardcover. Viii, 355p : ill ; 27cm. Companion volume to: Early visual learning. Includes bibliographical references and index. - Some of the fundamental constraints of automated machine vision have been the inability to automatically adapt parameter settin…gs or utilize previous adaptations in changing environments. Symbolic Visual Learning presents research which adds visual learning capabilities to computer vision systems. Using this state-of-the-art recognition technology, the outcome is different adaptive recognition systems that can measure their own performance, learn from their experience and outperform conventional static designs. Written as a companion volume to Early Visual Learning (edited by S. Nayar and T. Poggio), this book is intended for researchers and students in machine vision and machine learning. Condition : very good copy. ISBN 9780195098709. Keywords : PSYCHOLOGY.

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Da: Grand Eagle Retail, Bensenville, U.S.A.Grand Eagle Retail
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EUR 53,78
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Hardcover. Condizione: new. Hardcover. This book presents recent breakthroughs in the field of Learning-from-Observation (LfO) resulting from advancement in large language models (LLM) and reinforcement learning (RL) and positions it in the context of historical developments in the area. LfO involves observing human behaviors an…d generating robot actions that mimic these behaviors. While LfO may appear similar, on the surface, to Imitation Learning (IL) in the machine learning community and Programing-by-Demonstration (PbD) in the robotics community, a significant difference lies in the fact that these methods directly imitate human hand movements, whereas LfO encodes human behaviors into the abstract representations and then maps these representations onto the currently available hardware (individual body) of the robot, thus indirectly mimicking them. This indirect imitation allows for absorbing changes in the surrounding environment and differences in robot hardware. Additionally, by passing through this abstract representation, filtering can occur, distinguishing between important and less important aspects of human behavior, enabling imitation with fewer demonstrations and less demanding demonstrations. The authors have been researching the LfO paradigm for the past decade or so. Previously, the focus was primarily on designing necessary and sufficient task representations to define specific task domains such as assembly of machine parts, knot-tying, and human dance movements. Recent advancements in Generative Pre-trained Transformers (GPT) and RL have led to groundbreaking developments in methods to obtain and map these abstract representations. By utilizing GPT, the authors can automatically generate abstract representations from videos, and by employing RL-trained agent libraries, implementing robot actions becomes more feasible. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

Learning-from-observation 2.0: Automatic Acquisition of Robot Behavior from Human Demonstration
Ikeuchi, Katsushi/ Wake, Naoki/ Takamatsu, Jun/ Sasabuchi, Kazuhiro
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Da: Revaluation Books, Exeter, Regno UnitoRevaluation Books
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EUR 41,75
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Hardcover. Condizione: Brand New. 220 pages. 9.45x6.62x9.69 inches. In Stock.

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Da: Vivarium, LLC, Silverado, U.S.A.Vivarium, LLC
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Hardcover. Condizione: Near Fine. 8vo - over 7¾ - 9¾" tall. 504pp. NF/HC. Includes DVD "Bayon Digital Archive Project".

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Da: Books Puddle, New York, U.S.A.Books Puddle
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Condizione: New. pp. 540.

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Da: Majestic Books, Hounslow, Regno UnitoMajestic Books
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EUR 53,49
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Condizione: New. pp. 540 Illus.

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Da: Biblios, frankfurt am main, GermaniaBiblios
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Condizione: New. pp. 540.

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Da: SMASS Sellers, IRVING, U.S.A.SMASS Sellers
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Condizione: New. Brand New Original US Edition. Customer service! Satisfaction Guaranteed.

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Da: Poverty Hill Books, Mt. Prospect, U.S.A.Poverty Hill Books
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EUR 66,93
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Hardcover. Condizione: New. HARDCOVER, BRAND NEW COPY, Perfect Shape, No Black Remainder Mark,Fast Shipping With Online Tracking, International Orders shipped Global Priority Air Mail, All orders handled with care and shipped promptly in secure packaging, we ship Mon-Sat and send shipment confirmation emails. Our customer servic…e is friendly, we answer emails fast, accept returns and work hard to deliver 100% Customer Satisfaction.

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Da: Basi6 International, Irving, U.S.A.Basi6 International
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Condizione: Brand New. New. US edition. Expediting shipping for all USA and Europe orders excluding PO Box. Excellent Customer Service.

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Da: CitiRetail, Stevenage, Regno UnitoCitiRetail
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Hardcover. Condizione: new. Hardcover. This book presents recent breakthroughs in the field of Learning-from-Observation (LfO) resulting from advancement in large language models (LLM) and reinforcement learning (RL) and positions it in the context of historical developments in the area. LfO involves observing human behaviors an…d generating robot actions that mimic these behaviors. While LfO may appear similar, on the surface, to Imitation Learning (IL) in the machine learning community and Programing-by-Demonstration (PbD) in the robotics community, a significant difference lies in the fact that these methods directly imitate human hand movements, whereas LfO encodes human behaviors into the abstract representations and then maps these representations onto the currently available hardware (individual body) of the robot, thus indirectly mimicking them. This indirect imitation allows for absorbing changes in the surrounding environment and differences in robot hardware. Additionally, by passing through this abstract representation, filtering can occur, distinguishing between important and less important aspects of human behavior, enabling imitation with fewer demonstrations and less demanding demonstrations. The authors have been researching the LfO paradigm for the past decade or so. Previously, the focus was primarily on designing necessary and sufficient task representations to define specific task domains such as assembly of machine parts, knot-tying, and human dance movements. Recent advancements in Generative Pre-trained Transformers (GPT) and RL have led to groundbreaking developments in methods to obtain and map these abstract representations. By utilizing GPT, the authors can automatically generate abstract representations from videos, and by employing RL-trained agent libraries, implementing robot actions becomes more feasible. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.

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Da: GreatBookPrices, Columbia, U.S.A.GreatBookPrices
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Condizione: New.

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Da: Lucky's Textbooks, Dallas, U.S.A.Lucky's Textbooks
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Condizione: New.

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- Edizione Internazionale
Da: UK BOOKS STORE, London, Regno UnitoUK BOOKS STORE
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EUR 105,03
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Condizione: New. Brand New! Fast Delivery This is an International Edition and ship within 24-48 hours. Deliver by FedEx and Dhl, & Aramex, UPS, & USPS and we do accept APO and PO BOX Addresses. Order can be delivered worldwide within 6-10 days and we do have flat rate for up to 2LB. Extra shipping charges will be requested if t…he Book weight is more than 5 LB. This Item May be shipped from India, United states & United Kingdom. Depending on your location and availability.

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Da: AHA-BUCH GmbH, Einbeck, GermaniaAHA-BUCH GmbH
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EUR 42,79
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Buch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book presents recent breakthroughs in the field of Learning-from-Observation (LfO) resulting from advancement in large language models (LLM) and reinforcement learning (RL) and positions it in the context of historical developments in the area. LfO…involves observing human behaviors and generating robot actions that mimic these behaviors. While LfO may appear similar, on the surface, to Imitation Learning (IL) in the machine learning community and Programing-by-Demonstration (PbD) in the robotics community, a significant difference lies in the fact that these methods directly imitate human hand movements, whereas LfO encodes human behaviors into the abstract representations and then maps these representations onto the currently available hardware (individual body) of the robot, thus indirectly mimicking them. This indirect imitation allows for absorbing changes in the surrounding environment and differences in robot hardware. Additionally, by passing through this abstract representation, filtering can occur, distinguishing between important and less important aspects of human behavior, enabling imitation with fewer demonstrations and less demanding demonstrations. The authors have been researching the LfO paradigm for the past decade or so. Previously, the focus was primarily on designing necessary and sufficient task representations to define specific task domains such as assembly of machine parts, knot-tying, and human dance movements. Recent advancements in Generative Pre-trained Transformers (GPT) and RL have led to groundbreaking developments in methods to obtain and map these abstract representations. By utilizing GPT, the authors can automatically generate abstract representations from videos, and by employing RL-trained agent libraries, implementing robot actions becomes more feasible.

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Da: AussieBookSeller, Truganina, AustraliaAussieBookSeller
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Hardcover. Condizione: new. Hardcover. This book presents recent breakthroughs in the field of Learning-from-Observation (LfO) resulting from advancement in large language models (LLM) and reinforcement learning (RL) and positions it in the context of historical developments in the area. LfO involves observing human behaviors an…d generating robot actions that mimic these behaviors. While LfO may appear similar, on the surface, to Imitation Learning (IL) in the machine learning community and Programing-by-Demonstration (PbD) in the robotics community, a significant difference lies in the fact that these methods directly imitate human hand movements, whereas LfO encodes human behaviors into the abstract representations and then maps these representations onto the currently available hardware (individual body) of the robot, thus indirectly mimicking them. This indirect imitation allows for absorbing changes in the surrounding environment and differences in robot hardware. Additionally, by passing through this abstract representation, filtering can occur, distinguishing between important and less important aspects of human behavior, enabling imitation with fewer demonstrations and less demanding demonstrations. The authors have been researching the LfO paradigm for the past decade or so. Previously, the focus was primarily on designing necessary and sufficient task representations to define specific task domains such as assembly of machine parts, knot-tying, and human dance movements. Recent advancements in Generative Pre-trained Transformers (GPT) and RL have led to groundbreaking developments in methods to obtain and map these abstract representations. By utilizing GPT, the authors can automatically generate abstract representations from videos, and by employing RL-trained agent libraries, implementing robot actions becomes more feasible. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.

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Da: GreatBookPrices, Columbia, U.S.A.GreatBookPrices
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Da: Books Puddle, New York, U.S.A.Books Puddle
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Condizione: New. pp. 236.

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Condizione: Sehr gut. Zustand: Sehr gut | Seiten: 504 | Sprache: Englisch | Produktart: Bücher | Keine Beschreibung verfügbar.

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Da: Kennys Bookshop and Art Galleries Ltd., Galway, IrlandaKennys Bookshop and Art Galleries Ltd.
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Condizione: New. Summarizes the results of the editors' modeling-from-reality (MFR) project. This book is suitable for a secondary text in a graduate-level course, and as a reference for researchers and practitioners in industry. Editor(s): Ikeuchi, Katsushi; Sato, Yoichi. Series: The Springer International Series in Engineering… and Computer Science. Num Pages: 199 pages, biography. BIC Classification: UYQV. Category: (P) Professional & Vocational; (UP) Postgraduate, Research & Scholarly; (UU) Undergraduate. Dimension: 235 x 155 x 14. Weight in Grams: 509. . 2001. Hardback. . . . .

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Da: Ria Christie Collections, Uxbridge, Regno UnitoRia Christie Collections
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Da: GreatBookPricesUK, Woodford Green, Regno UnitoGreatBookPricesUK
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Da: Kennys Bookstore, Olney, U.S.A.Kennys Bookstore
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EUR 167,44
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Condizione: New. Summarizes the results of the editors' modeling-from-reality (MFR) project. This book is suitable for a secondary text in a graduate-level course, and as a reference for researchers and practitioners in industry. Editor(s): Ikeuchi, Katsushi; Sato, Yoichi. Series: The Springer International Series in Engineering… and Computer Science. Num Pages: 199 pages, biography. BIC Classification: UYQV. Category: (P) Professional & Vocational; (UP) Postgraduate, Research & Scholarly; (UU) Undergraduate. Dimension: 235 x 155 x 14. Weight in Grams: 509. . 2001. Hardback. . . . . Books ship from the US and Ireland.