Katsushi ikeuchi (128 resultados)
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Librería: Better World Books, Mishawaka, IN, Estados Unidos de AmericaBetter World Books
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EUR 20,60
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Condición: 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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Librería: Midtown Scholar Bookstore, Harrisburg, PA, Estados Unidos de AmericaMidtown Scholar Bookstore
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EUR 40,29
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Hardcover. Condición: Good. some shelfwear/edgewear but still NICE! - may have remainder mark or previous owner's name Standard-sized.
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Librería: Hay-on-Wye Booksellers, Hay-on-Wye, HEREF, Reino UnidoHay-on-Wye Booksellers
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EUR 18,09
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Condición: Very Good.
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Librería: Kloof Booksellers & Scientia Verlag, Amsterdam, HolandaKloof Booksellers & Scientia Verlag
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EUR 20,95
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Condición: 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 setting…s 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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Librería: Grand Eagle Retail, Bensenville, IL, Estados Unidos de AmericaGrand Eagle Retail
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EUR 54,53
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Hardcover. Condición: 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 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. 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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Librería: Revaluation Books, Exeter, Reino UnidoRevaluation Books
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EUR 42,06
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Hardcover. Condición: Brand New. 220 pages. 9.45x6.62x9.69 inches. In Stock.
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Librería: Vivarium, LLC, Silverado, CA, Estados Unidos de AmericaVivarium, LLC
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EUR 54,32
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Hardcover. Condición: Near Fine. 8vo - over 7¾ - 9¾" tall. 504pp. NF/HC. Includes DVD "Bayon Digital Archive Project".
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Librería: Poverty Hill Books, Mt. Prospect, IL, Estados Unidos de AmericaPoverty Hill Books
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EUR 67,85
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Hardcover. Condición: 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 service… is friendly, we answer emails fast, accept returns and work hard to deliver 100% Customer Satisfaction.
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Librería: Basi6 International, Irving, TX, Estados Unidos de AmericaBasi6 International
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EUR 82,48
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Condición: Brand New. New. US edition. Expediting shipping for all USA and Europe orders excluding PO Box. Excellent Customer Service.
Learning-from-Observation 2.0: Automatic Acquisition of Robot Behavior from Human Demonstration (Synthesis Lectures on Computer Vision)
Ikeuchi, Katsushi; Wake, Naoki; Takamatsu, Jun; Sasabuchi, Kazuhiro
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Librería: Books Puddle, New York, NY, Estados Unidos de AmericaBooks Puddle
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EUR 79,13
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Condición: New.
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Librería: Basi6 International, Irving, TX, Estados Unidos de AmericaBasi6 International
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EUR 84,35
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Condición: Brand New. New. US edition. Expediting shipping for all USA and Europe orders excluding PO Box. Excellent Customer Service.
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Librería: Romtrade Corp., STERLING HEIGHTS, MI, Estados Unidos de AmericaRomtrade Corp.
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EUR 84,88
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Condición: 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.
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Librería: Books Puddle, New York, NY, Estados Unidos de AmericaBooks Puddle
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EUR 83,35
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Condición: New. pp. 540.
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Librería: SMASS Sellers, IRVING, TX, Estados Unidos de AmericaSMASS Sellers
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EUR 88,09
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Condición: New. Brand New Original US Edition. Customer service! Satisfaction Guaranteed.
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Librería: Majestic Books, Hounslow, Reino UnidoMajestic Books
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EUR 82,77
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Condición: New. pp. 540 Illus.
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Librería: CitiRetail, Stevenage, Reino UnidoCitiRetail
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EUR 45,67
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Hardcover. Condición: 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 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. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
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Librería: Biblios, frankfurt am main, HESSE, AlemaniaBiblios
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EUR 81,06
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Condición: New. pp. 540.
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- Edición internacional
Librería: UK BOOKS STORE, London, LONDO, Reino UnidoUK BOOKS STORE
Contactar con el vendedorVendedor de 5 estrellasEdición internacionalCondición: Nuevo
EUR 106,88
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Condición: 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 th…e 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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Librería: GreatBookPrices, Columbia, MD, Estados Unidos de AmericaGreatBookPrices
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EUR 106,62
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Condición: New.
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Librería: Lucky's Textbooks, Dallas, TX, Estados Unidos de AmericaLucky's Textbooks
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EUR 105,41
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Condición: New.
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Librería: AHA-BUCH GmbH, Einbeck, AlemaniaAHA-BUCH GmbH
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EUR 42,79
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Buch. Condición: 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 i…nvolves 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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Librería: AussieBookSeller, Truganina, VIC, AustraliaAussieBookSeller
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EUR 81,71
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Hardcover. Condición: 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 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. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
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Librería: GreatBookPrices, Columbia, MD, Estados Unidos de AmericaGreatBookPrices
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EUR 121,89
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Condición: As New. Unread book in perfect condition.
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Librería: Ria Christie Collections, Uxbridge, Reino UnidoRia Christie Collections
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EUR 116,46
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EUR 116,45
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Librería: Buchpark, Trebbin, AlemaniaBuchpark
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EUR 33,28
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Condición: Sehr gut. Zustand: Sehr gut | Seiten: 504 | Sprache: Englisch | Produktart: Bücher | Keine Beschreibung verfügbar.
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EUR 129,26
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Librería: Kennys Bookshop and Art Galleries Ltd., Galway, GY, IrlandaKennys Bookshop and Art Galleries Ltd.
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EUR 133,74
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Condición: 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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Librería: Books Puddle, New York, NY, Estados Unidos de AmericaBooks Puddle
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EUR 148,73
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Condición: New. pp. 236.
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EUR 150,24
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Condición: New.
