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Kategorie szczegółowe BISAC

Building Computer Vision Applications Using Artificial Neural Networks: With Examples in OpenCV and TensorFlow with Python

ISBN-13: 9781484298657 / Miękka / 2023 / 527 str.

Shamshad Ansari
Building Computer Vision Applications Using Artificial Neural Networks: With Examples in OpenCV and TensorFlow with Python Shamshad Ansari 9781484298657 APress - książkaWidoczna okładka, to zdjęcie poglądowe, a rzeczywista szata graficzna może różnić się od prezentowanej.

Building Computer Vision Applications Using Artificial Neural Networks: With Examples in OpenCV and TensorFlow with Python

ISBN-13: 9781484298657 / Miękka / 2023 / 527 str.

Shamshad Ansari
cena 241,50
(netto: 230,00 VAT:  5%)

Najniższa cena z 30 dni: 231,29
Termin realizacji zamówienia:
ok. 22 dni roboczych.

Darmowa dostawa!
Kategorie:
Informatyka, Programowanie
Kategorie BISAC:
Computers > Artificial Intelligence - General
Computers > Languages - Python
Computers > Programming - Open Source
Wydawca:
APress
ISBN-13:
9781484298657
Rok wydania:
2023
Ilość stron:
527
Wymiary:
25.4 x 17.8
Oprawa:
Miękka
Dodatkowe informacje:
Wydanie ilustrowane


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).

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

 

You will:

  • 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



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