Building Computer Vision Applications Using Artificial Neural Networks: With Examples in Opencv and Tensorflow with Python

Computer vision is constantly evolving, and this book has been updated to reflect new topics that have emerged in the field since the first edition's publication. All code used in the book has also been fully updated.

This second edition features new material covering image manipulation practices, image segmentation, feature extraction, and object identification using real-life scenarios to help reinforce each concept. These topics are essential for building advanced computer vision applications, and you'll gain a thorough understanding of them. The book's source code has been updated from TensorFlow 1.x to 2.x, and includes step-by-step examples using both OpenCV and TensorFlow with Python.

Upon completing this book, you'll have the knowledge and skills to build your own computer vision applications using neural networks

What You Will Learn

• Understand image processing, manipulation techniques, and feature extraction methods
• Work with convolutional neural networks (CNN), single-shot detector (SSD), and YOLO
• Utilize large scale model development and cloud infrastructure deployment
• Gain an overview of FaceNet neural network architecture and develop a facial recognition system

Who This Book Is For

Those who possess a solid understanding of Python programming and wish to gain an understanding of computer vision and machine learning. It will prove beneficial to data scientists, deep learning experts, and students.

電腦視覺不斷演進，本書已更新以反映自第一版出版以來在該領域出現的新主題。書中使用的所有程式碼也已完全更新。

第二版新增了有關圖像處理實踐、圖像分割、特徵提取和使用真實場景進行物體識別的新材料，以幫助加強每個概念。這些主題對於構建高級電腦視覺應用程序至關重要，您將對它們有全面的了解。本書的源代碼已從TensorFlow 1.x更新到2.x，並包括使用OpenCV和TensorFlow的Python的逐步示例。

完成本書後，您將具備使用神經網絡構建自己的電腦視覺應用程序的知識和技能。

您將學到什麼：
- 理解圖像處理、操作技術和特徵提取方法
- 使用卷積神經網絡（CNN）、單次檢測器（SSD）和YOLO進行工作
- 利用大規模模型開發和雲基礎架構部署
- 瞭解FaceNet神經網絡架構並開發人臉識別系統

本書適合對Python編程有扎實理解並希望瞭解電腦視覺和機器學習的人士。對於數據科學家、深度學習專家和學生來說，這將是有益的資源。

Shamshad (Sam) Ansari is an author, inventor, and thought leader in the fields of computer vision, machine learning, artificial intelligence, and cognitive science. He has extensive experience in high scale, distributed, and parallel computing. Sam currently serves as an Adjunct Professor at George Mason University, teaching graduate- level programs within the Data Analytics Engineering department of the Volgenau School of Engineering. His areas of instruction encompass machine learning, natural language processing, and computer vision, where he imparts his knowledge and expertise to aspiring professionals.

Having authored multiple publications on topics such as machine learning, RFID, and high-scale enterprise computing, Sam's contributions extend beyond academia. He holds four US patents related to healthcare AI, showcasing his innovative mindset and practical application of technology.

Throughout his extensive 20+ years of experience in enterprise software development, Sam has been involved with several tech startups and early-stage companies. He has played pivotal roles in building and expanding tech teams from the ground up, contributing to their eventual acquisition by larger organizations. At the beginning of his career, he worked with esteemed institutions such as the US Department of Defense (DOD) and IBM, honing his skills and knowledge in the industry.

Currently, Sam serves as the President and CEO of Accure, Inc., an AI company that he founded. He is the creator, architect, and a significant contributor to Momentum AI, a no-code platform that encompasses data engineering, machine learning, AI, MLOps, data warehousing, and business intelligence. Throughout his career, Sam has made notable contributions in various domains including healthcare, retail, supply chain, banking and finance, and manufacturing. Demonstrating his leadership skills, he has successfully managed teams of software engineers, data scientists, and DevSecOps professionals, leading them to deliver exceptional results. Sam earned his bachelor's degree in engineering from Birsa Institute of Technology (BIT) Sindri and subsequently a Master's degree from the prestigious Indian Institute of Information Technology and Management Kerala (IIITM-K).

Shamshad (Sam) Ansari是一位作家、發明家和計算機視覺、機器學習、人工智能和認知科學領域的思想領袖。他在高規模、分散和並行計算方面擁有豐富的經驗。Sam目前擔任喬治梅森大學的兼職教授，教授沃爾根瑙工程學院數據分析工程系的研究生課程。他的教學範圍包括機器學習、自然語言處理和計算機視覺，他將自己的知識和專業知識傳授給有抱負的專業人士。

Sam在機器學習、射頻識別（RFID）和高規模企業計算等主題上撰寫了多篇論文，他的貢獻超越了學術界。他擁有四項與醫療人工智能相關的美國專利，展示了他創新的思維方式和技術的實際應用。

在超過20年的企業軟件開發經驗中，Sam參與了幾家初創技術公司和早期公司。他在從頭開始建立和擴展技術團隊方面發揮了關鍵作用，並促成了這些公司被更大組織收購。在職業生涯初期，他曾與美國國防部和IBM等知名機構合作，磨練了自己在行業中的技能和知識。

目前，Sam擔任他創立的AI公司Accure, Inc.的總裁兼首席執行官。他是Momentum AI的創造者、架構師和重要貢獻者，這是一個無代碼平台，涵蓋數據工程、機器學習、人工智能、MLOps、數據倉儲和商業智能。在職業生涯中，Sam在醫療保健、零售、供應鏈、銀行和金融以及製造等各個領域做出了顯著貢獻。他展示了他的領導才能，成功管理軟件工程師、數據科學家和DevSecOps專業人員團隊，帶領他們取得了優異的成果。Sam在Birsa Institute of Technology (BIT) Sindri獲得了工程學士學位，隨後在印度信息技術和管理學院喀拉拉邦分校（IIITM-K）獲得了碩士學位。