Advancement of Deep Learning and its Applications in Object Detection and Recognition

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Advancement of Deep Learning and its Applications in Object Detection and Recognition

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  • 製本 Hardcover:ハードカバー版/ページ数 286 p.
  • 言語 ENG
  • 商品コード 9788770227025
  • DDC分類 006.31

Full Description

Object detection is a basic visual identification problem in computer vision that has been explored extensively over the years. Visual object detection seeks to discover objects of specific target classes in a given image with pinpoint accuracy and apply a class label to each object instance. Object recognition strategies based on deep learning have been intensively investigated in recent years as a result of the remarkable success of deep learning-based image categorization.

In this book, we go through in detail detector architectures, feature learning, proposal generation, sampling strategies, and other issues that affect detection performance.

The book describes every newly proposed novel solution but skips through the fundamentals so that readers can see the field's cutting edge more rapidly. Moreover, unlike prior object detection publications, this project analyses deep learning-based object identification methods systematically and exhaustively, and also gives the most recent detection solutions and a collection of noteworthy research trends.

The book focuses primarily on step-by-step discussion, an extensive literature review, detailed analysis and discussion, and rigorous experimentation results. Furthermore, a practical approach is displayed and encouraged.

Contents

1. Recent Advances in Video Captioning with Object Detection 2. A Deep Learning-based Framework for COVID-19 Identification using Chest X-Ray Images 3. Faster Region-based Convolutional Neural Networks for the Detection of Surface Defects in Aluminum Tubes 4. Real Time Face Detection-based Automobile Safety System Using Computer Vision and Supervised Machine Learning 5. Texture Feature Descriptors for Analyzing Facial Patterns in Facial Expression Recognition System 6. A Texture Features-based Method to Detect Face Spoofing 7. Enhanced Tal Hassner and Gil Levi Approach for Prediction of Age and Gender with Mask and Mask less 8. A Brief Overview of Recent Techniques in Crowd Counting and Density Estimation 9. Recent Trends in 2D Object Detection and Applications in Video Event Recognition 10. Survey on Vehicle Detection, Identification and Count using CNN-based YOLO Architecture and Related Applications 11. An Extensive Study on Object Detection and Recognition using Deep Learning Techniques 12. A Comprehensive Review on State-Of-The-Art Techniques of Image Inpainting 13. Hybrid Leaf Generative Adversarial Networks Scheme For Classification of Tomato Leaves—Early Blight Disease or Healthy

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