OBJECT DETECTION BY STEREO VISION IMAGES Since both theoretical and
practical aspects of the developments in this field of research are
explored, including recent state-of-the-art technologies and
research opportunities in the area of object detection, this book
will act as a good reference for practitioners, students, and
researchers. Current state-of-the-art technologies have opened up
new opportunities in research in the areas of object detection and
recognition of digital images and videos, robotics, neural
networks, machine learning, stereo vision matching algorithms, soft
computing, customer prediction, social media analysis,
recommendation systems, and stereo vision. This book has been
designed to provide directions for those interested in researching
and developing intelligent applications to detect an object and
estimate depth. In addition to focusing on the performance of the
system using high-performance computing techniques, a technical
overview of certain tools, languages, libraries, frameworks, and
APIs for developing applications is also given. More specifically,
detection using stereo vision images/video from its developmental
stage up till today, its possible applications, and general
research problems relating to it are covered. Also presented are
techniques and algorithms that satisfy the peculiar needs of stereo
vision images along with emerging research opportunities through
analysis of modern techniques being applied to intelligent systems.
Audience Researchers in information technology looking at robotics,
deep learning, machine learning, big data analytics, neural
networks, pattern & data mining, and image and object
recognition. Industrial sectors include automotive electronics,
security and surveillance systems, and online retailers.
General
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