Computer Vision

《MATLAB圖像處理：程序實現與模塊化仿真》深入淺出地介紹了MATLAB 2012計算機視覺工具箱（Computer Vision System）、數字圖像處理工具箱的最新功能，并以此為編程工具闡述了數字圖像／視頻的基礎理論、關鍵技術、應用實例、解決方案、發展前沿。《MATLAB圖像處理：程序實現與模塊化仿真》共8章，內容包括：MATLAB數字圖像／視頻處理

The authors of "OpenCV" explain how to put computer vision to work. They bring readers up to speed with the latest updates in the field and show them how to program with existing free code.

Bridges the gap between virtual reality and computer vision in manufacturingWhat will it take to make virtual manufacturing a reality? In this groundbreaking book, leading VR researchers reveal the la

This book brings together novel concepts in machine vision, computer graphics, and threedimensional modelling, in solving real practical inspection problems. Automated inspection of three-dimensional

In 1936, when he was just twenty-four years old, Alan Turing wrote a remarkable paper in which he outlined the theory of computation, laying out the ideas that underlie all modern computers. This grou

Image processing is concerned with the analysis and manipulation of images by computer. Providing a thorough treatment of image processing with an emphasis on those aspects most used in computer graph

Smartphones, nuclear warheads, moon bases, computers . . . all bear the fingerprints of one remarkable man: John von Neumann. Born in Budapest in 1903, he moved to America in 1930 and--in his work as mathematician, physicist, computer scientist, and engineer--became one of the most influential scientists of the century. Von Neumann was instrumental in the Manhattan Project and the design of the atom bomb; he helped formulate game theory, the bedrock of Cold War geopolitics and modern economic theory; he created the programmable digital computer; he prophesized the potential of nanotechnology; and, from his deathbed, he outlined a vision of artificial intelligence.In telling the story of Von Neumann's life and ideas, Ananyo Bhattacharya explores how a combination of genius and historical circumstance allowed one man to sweep through so many different fields of science, sparking revolutions wherever he went. The Man from the Future is a thrilling biography of a visionary thinker who shap

【本書特色】 最貼近新手的深度學習理論及應用全方位入門書！ ✪學習必備理論，打好基礎，新手不怕被過多的數學式嚇跑。 ✪使用PyTorch直覺易懂且強大的深度學習框架，開始應用的第一步。 ✪了解自然語言處理、電腦視覺與強化學習等三大領域經典應用與實作，領略深度學習的強大。 ✪兼顧理論與實作，而非偏頗一方，培養讀者較全面的理解。 ✪包含經典學術論文與知名專案技術講解，幫助讀者掌握此技術所能到達的高度。 ✪每章末提供自我檢驗題目，幫助理解與統整各章概念。 【內容簡介】 本書內容改編自第12屆iT邦幫忙鐵人賽AI & Data組冠軍系列文章《Knock Knock！Deep Learning》，是專為深度學習初學者所規劃的內容，旨在以淺顯易懂的文字，帶領深度學習領域的新手度過入門撞牆期。內容從深度學習的基本理論開始，並以PyTorch框架的介紹過渡至應用篇，最後以自然語言處理、電腦視覺與強化學習等三大領域的經典論文與實作專案收尾，循序漸進且去蕪存菁。本書會帶入許多故事性的敘述和插圖，結合作者自身在史丹佛大學修讀碩士期間的學習心得，以及深度學習發展相關的故事，期使本書讀起來不會如教科書一樣厚重，亦不會像網路上的技術文章一般零散無脈絡，讓讀者對深度學習領域的發展有一定的概念。 【內容重點】 ✪了解深度學習的基礎理論以及必備的實作知識與工具 內容從人類的神經網路開始，介紹深度學習與其相似之處，並理解神經網路的學習步驟，同時也介紹一些必備的實作知識與工具，以具備基本的實作工程技能。 ✪入門深度學習框架PyTorch 內容介紹語法簡潔、好上手且在學術界流行的PyTorch框架，著重實作與應用。 ✪深度學習×自然語言處理×電腦視覺×強化學習 內容會依序談到深度學習在三方面的應用，如自然語言處理（Natural Language Processing，NLP )、電腦視覺（Computer Vision，CV )、強化學習（Reinforcement Learning，RL )。除了基本簡介外，還會介紹一些基本實作和改變世界的技術成果。 【適用讀者】 ✪對深度學習有興趣，但還不知道它是什麼、能做什麼的新手。 ✪零散讀過深度學習相關文章，但仍有知識缺口的入門者。 ✪被教科書中龐大的數學理論嚇到，而對深度學習卻步的讀者。 ✪正在上學校的深度學習課程，但不知道實作從何開始的學生。

Many machine learning algorithms require real-valued feature vectors of data instances as inputs. By projecting data into vector spaces, representation learning techniques have achieved promising performance in many areas such as computer vision and natural language processing. There is also a need to learn representations for discrete relational data, namely networks or graphs. Network Embedding (NE) aims at learning vector representations for each node or vertex in a network to encode the topologic structure. Due to its convincing performance and efficiency, NE has been widely applied in many network applications such as node classification and link prediction.This book provides a comprehensive introduction to the basic concepts, models, and applications of network representation learning (NRL). The book starts with an introduction to the background and rising of network embeddings as a general overview for readers. Then it introduces the development of NE techniques by presenting se

Network flow theory has been used across a number of disciplines, including theoretical computer science, operations research, and discrete math, to model not only problems in the transportation of goods and information, but also a wide range of applications from image segmentation problems in computer vision to deciding when a baseball team has been eliminated from contention. This graduate text and reference presents a succinct, unified view of a wide variety of efficient combinatorial algorithms for network flow problems, including many results not found in other books. It covers maximum flows, minimum-cost flows, generalized flows, multicommodity flows, and global minimum cuts and also presents recent work on computing electrical flows along with recent applications of these flows to classical problems in network flow theory.

Computer scientists describe the current understanding and practice of machine learning, both supervised and unsupervised, in a range of fields. They cover mobile vision for a plant biometric syste

Enhance your understanding of Computer Vision and image processing by developing real-world projects in OpenCV 3About This BookGet to grips with the basics of Computer Vision and image processingThis

Expand your knowledge of computer vision by building amazing projects with OpenCV 3About This BookBuild computer vision projects to capture high-quality image data, detect and track objects, process t

Build real-world computer vision applications and develop cool demos using OpenCV for PythonAbout This BookLearn how to apply complex visual effects to images using geometric transformations and image

If you are a Java developer who is new to computer vision and would like to learn through application development, then this book is for you. You are expected to have a mobile device running Android 2

This book reviews the algorithms for processing geometric data, with a practical focus on important techniques not covered by traditional courses on computer vision and computer graphics. Features: pr

An ongoing effort is being made in the field of computer vision to refine algorithms for optimal/better performance, which can mean reliability and increased computational speed. This is highly impor

In the areas of image processing and computer vision, there is a particular need for software that can, given an unfocused or motion-blurred image, infer the three-dimensional shape of a scene. This b

Papers from a spring 2005 conference describe the latest research in recognition, medical imaging, shape analysis and segmentation, early vision and stereo vision, scene analysis and tracking, intelli

This collection of 38 papers and 29 posters from the May 2004 conference reports on research and development activities in computer vision, robot vision, image processing, medical imaging, and pattern

Two important subproblems of computer vision are the detection and recognition of 2D objects in gray-level images. This book discusses the construction and training of models, computational approache

A renewed interest in the study of vision has attracted scholars from such diversefields as neuroscience, computer science, mathematics, physics, and philosophy. At the same time,the development of im

Computer vision seeks a process that starts with a noisy,ambiguous signal from a TV camera and ends with a high-leveldescription of discrete objects located in 3-dimensionalspace and identified in a

As the contributions to this book make clear, a fundamental change is taking place in the study of computational linguistics analogous to that which has taken place in the study of computer vision ove

A renewed interest in the study of vision has attracted scholars from such diverse fields as neuroscience, computer science, mathematics, physics and philosophy. At the same time, the development of i

This work integrates a twenty-year research program on the nature of high-level vision and mental imagery. It marshals insights and empirical results from computer vision, neuroscience, and cognitive

This book solves a long-standing problem in computer vision, the interpretation of line drawings and, in doing so answers many of the concerns raised by this problem, particularly with regard to error