{"product_id":"building-computer-vision-applications-using-artificial-neural-networks-with-examples-in-opencv-and-tensorflow-with-python-paperback","title":"Building Computer Vision Applications Using Artificial Neural Networks: With Examples in Opencv and Tensorflow with Python - Paperback","description":"\u003cp\u003eby \u003cb\u003eShamshad Ansari\u003c\/b\u003e (Author)\u003c\/p\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003eComputer 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.\u003c\/p\u003e \u003cp\u003eThis 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. \u003c\/p\u003e \u003cp\u003eUpon completing this book, you'll have the knowledge and skills to build your own computer vision applications using neural networks\u003c\/p\u003e \u003cp\u003e \u003c\/p\u003e \u003cp\u003e\u003cb\u003eWhat You Will Learn\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eUnderstand image processing, manipulation techniques, and feature extraction methods\u003c\/li\u003e\n\u003cli\u003eWork with convolutional neural networks (CNN), single-shot detector (SSD), and YOLO\u003c\/li\u003e\n\u003cli\u003eUtilize large scale model development and cloud infrastructure deployment\u003c\/li\u003e\n\u003cli\u003eGain an overview of FaceNet neural network architecture and develop a facial recognition system\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003e\u003c\/p\u003e \u003cp\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003eWho This Book Is For\u003c\/b\u003e\u003c\/p\u003e 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.\u003ch3\u003eBack Jacket\u003c\/h3\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003eComputer 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.\u003c\/p\u003e \u003cp\u003eThis 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. \u003c\/p\u003e \u003cp\u003eUpon completing this book, you'll have the knowledge and skills to build your own computer vision applications using neural networks\u003c\/p\u003e \u003cp\u003e \u003c\/p\u003e You will: \u003cp\u003e\u003c\/p\u003e \u003cp\u003e\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eUnderstand image processing, manipulation techniques, and feature extraction methods\u003c\/li\u003e\n\u003cli\u003eWork with convolutional neural networks (CNN), single-shot detector (SSD), and YOLO\u003c\/li\u003e\n\u003cli\u003eUtilize large scale model development and cloud infrastructure deployment\u003c\/li\u003e\n\u003cli\u003eGain an overview of FaceNet neural network architecture and develop a facial recognition system\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003e\u003c\/p\u003e \u003cp\u003e\u003c\/p\u003e\u003ch3\u003eAuthor Biography\u003c\/h3\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003e\u003cb\u003eShamshad (Sam) Ansari \u003c\/b\u003eis 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.\u003c\/p\u003e 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.\u003cp\u003e\u003c\/p\u003e \u003cp\u003eThroughout 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.\u003c\/p\u003e 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).\u003cdiv\u003e\n\u003cstrong\u003eNumber of Pages:\u003c\/strong\u003e 526\u003c\/div\u003e\u003cdiv\u003e\n\u003cstrong\u003eDimensions:\u003c\/strong\u003e 1.11 x 10 x 7 IN\u003c\/div\u003e\u003cdiv\u003e\n\u003cstrong\u003eIllustrated:\u003c\/strong\u003e Yes\u003c\/div\u003e\u003cdiv\u003e\n\u003cstrong\u003ePublication Date:\u003c\/strong\u003e November 18, 2023\u003c\/div\u003e","brand":"Books by splitShops","offers":[{"title":"Default Title","offer_id":42706332680255,"sku":"9781484298657","price":70.18,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0105\/8226\/1823\/files\/d19f17272b6890f0a1e7e16cdc8f6ec8.webp?v=1765040042","url":"https:\/\/dhl-adrianne.myshopify.com\/products\/building-computer-vision-applications-using-artificial-neural-networks-with-examples-in-opencv-and-tensorflow-with-python-paperback","provider":"BBB","version":"1.0","type":"link"}