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Product Details 基本信息 ISBN-13 书号 9783030710538 Format 版本 平装-胶订 Pages Number 页数 948页 Publisher 出版社 Springer Publication Date 出版日期 1800-01-01 Product Dimensions 商品尺寸 9.21 x 6.14 x 1.87 Shipping Weight 商品重量 2.86 Language 语种 其它(含多语)
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【预订】Computer Vision: Three-dimensional Reconstruction Techni 【全球购】进口原版图书,一般10-12周左右到国内
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预订 Many Voices, One Vision: The Early Years of the World Her 【全球购】进口原版图书,一般5-8周左右到国内
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海外直订Hidden Link Between Vision and Learning 视觉和学习之间隐藏的联系
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【预售 按需印刷】Building Computer Vision Projects with Op
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海外直订3D Computer Vision: Efficient Methods and Applications 三
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【预订】Guide to 3D Vision Computation 9783319839554 国外库房发货,通常付款后3-5周到货!
Product Details 基本信息 ISBN-13 书号 9783319839554 Author 作者 Kenichi Kanatani Okayama University Okayama Japan Format 版本 平装-胶订 Pages Number 页数 null页 Publisher 出版社 Springer Berlin Heidelberg Publication Date 出版日期 2018-07-05 Language 语种 其它(含多语) Book Contents 内容简介 This classroom-tested and easy-to-understand textbook/reference describes the state of the art in 3D reconstruction from multiple images, taking into consideration all aspects of programming and implementation. Unlike other computer vision textbooks, this guide takes a unique approach in which the initial focus is on practical application and the procedures necessary to actually build a computer vision system. The theoretical background is then briefly explained afterwards, highlighting how one can quickly and simply obtain the desired result without knowing the derivation of the mathematical detail. Featur
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海外直订Exploratory Vision: The Active Eye 探索性视觉:主动眼
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海外直订Robotics, Vision and Control 机器人,视觉和控制
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预售 按需印刷 A new vision in teaching 北京发货,付款后10天内发货
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海外直订Industry 4.0 Vision for the Supply of Energy and Materia
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【预订】Practical Computer Vision Applications Using Deep Learni 美国库房发货,通常付款后3-5周到货!
Product Details 基本信息 ISBN-13 书号 9781484241660 Author 作者 Ahmed Fawzy Gad Format 版本 平装-胶订 Pages Number 页数 405页 Publisher 出版社 Apress Publication Date 出版日期 2018-12-06 Language 语种 英语 Book Contents 内容简介 Deploy deep learning applications into production across multiple platforms. You will work on computer vision applications that use the convolutional neural network (CNN) deep learning model and Python. This book starts by explaining the traditional machine-learning pipeline, where you will analyze an image dataset. Along the way you will cover artificial neural networks (ANNs), building one from scratch in Python, before optimizing it using genetic algorithms. For automating the process, the book highlights the limitations of traditional hand-crafted features for computer vision and why the CNN deep-learning model is the state-of-art solution. CNNs are discussed from scr
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