@article{1484355,
      recid = {1484355},
      author = {Ansari, Shamshad,},
      title = {Building computer vision applications using artificial  neural networks : with examples in OpenCV and TensorFlow  with Python /},
      pages = {1 online resource (xxii, 526 pages) :},
      note = {Includes index.},
      abstract = {Computer vision is constantly evolving, and this book has  been updated to reflect new topics that have emerged in the  field since the first edition⁰́b9s 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  you⁰́b9ll gain a thorough understanding of them. The  book⁰́b9s 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, you⁰́b9ll 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.},
      url = {http://library.usi.edu/record/1484355},
      doi = {https://doi.org/10.1007/978-1-4842-9866-4},
}