Trending Bestseller

Object Detection with Deep Learning Models

Principles and Applications

No reviews yet Write a Review
Hardback
01 November 2022
$324.02
Ships in 3-5 business days

Delivery estimate

Hurry up! Current stock:

Object Detection with Deep Learning Models discusses recent advances in object detection and recognition using deep learning methods, which have achieved great success in the field of computer vision and image processing. It provides a systematic and methodical overview of the latest developments in deep learning theory and its applications to computer vision, illustrating them using key topics, including object detection, face analysis, 3D object recognition, and image retrieval.

The book offers a rich blend of theory and practice. It is suitable for students, researchers and practitioners interested in deep learning, computer vision and beyond and can also be used as a reference book. The comprehensive comparison of various deep-learning applications helps readers with a basic understanding of machine learning and calculus grasp the theories and inspires applications in other computer vision tasks.

Features:

  • A structured overview of deep learning in object detection
  • A diversified collection of applications of object detection using deep neural networks
  • Emphasize agriculture and remote sensing domains
  • Exclusive discussion on moving object detection
Product Details
ISBN-13
9781032074009
Author
S Poonkuntran
Publisher
Taylor & Francis Ltd
Published
01 November 2022
Format
Hardback

This product hasn't received any reviews yet. Be the first to review this product!

$324.02
Ships in 3-5 business days

Delivery estimate

Hurry up! Current stock:

Object Detection with Deep Learning Models

$324.02

Description

Object Detection with Deep Learning Models discusses recent advances in object detection and recognition using deep learning methods, which have achieved great success in the field of computer vision and image processing. It provides a systematic and methodical overview of the latest developments in deep learning theory and its applications to computer vision, illustrating them using key topics, including object detection, face analysis, 3D object recognition, and image retrieval.

The book offers a rich blend of theory and practice. It is suitable for students, researchers and practitioners interested in deep learning, computer vision and beyond and can also be used as a reference book. The comprehensive comparison of various deep-learning applications helps readers with a basic understanding of machine learning and calculus grasp the theories and inspires applications in other computer vision tasks.

Features:

  • A structured overview of deep learning in object detection
  • A diversified collection of applications of object detection using deep neural networks
  • Emphasize agriculture and remote sensing domains
  • Exclusive discussion on moving object detection