Computer Vision and Image Analysis for Industry 4.0
eBook - ePub

Computer Vision and Image Analysis for Industry 4.0

  1. 314 pages
  2. English
  3. ePUB (mobile friendly)
  4. Available on iOS & Android
eBook - ePub

Computer Vision and Image Analysis for Industry 4.0

About this book

Computer vision and image analysis are indispensable components of every automated environment. Modern machine vision and image analysis techniques play key roles in automation and quality assurance. Working environments can be improved significantly if we integrate computer vision and image analysis techniques. The more advancement in innovation and research in computer vision and image processing, the greater the efficiency of machines as well as humans. Computer Vision and Image Analysis for Industry 4.0 focuses on the roles of computer vision and image analysis for 4.0 IR-related technologies. The text proposes a variety of techniques for disease detection and prediction, text recognition and signature verification, image captioning, flood level assessment, crops classifications and fabrication of smart eye-controlled wheelchairs.

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Yes, you can access Computer Vision and Image Analysis for Industry 4.0 by Nazmul Siddique, Mohammad Shamsul Arefin, Md Atiqur Rahman Ahad, M. Ali Akber Dewan, Nazmul Siddique,Mohammad Shamsul Arefin,Md Atiqur Rahman Ahad,M. Ali Akber Dewan in PDF and/or ePUB format, as well as other popular books in Computer Science & Computer Science General. We have over one million books available in our catalogue for you to explore.

Table of contents

  1. Cover Page
  2. Half-Title Page
  3. Title Page
  4. Copyright Page
  5. Dedication Page
  6. Contents
  7. Preface
  8. Contributors
  9. Editors
  10. Chapter 1 ◾ BN-HTRd: A Benchmark Dataset for Document Level Offline Bangla Handwritten Text Recognition (HTR) and Line Segmentation
  11. Chapter 2 ◾ A New Approach Using a Convolutional Neural Network for Crop and Weed Classification
  12. Chapter 3 ◾ Lemon Fruit Detection and Instance Segmentation in an Orchard Environment Using Mask R-CNN and YOLOv5
  13. Chapter 4 ◾ A Deep Learning Approach in Detailed Fingerprint Identification
  14. Chapter 5 ◾ Probing Skin Lesions and Performing Classification of Skin Cancer Using EfficientNet while Resolving Class Imbalance Using SMOTE
  15. Chapter 6 ◾ Advanced GradCAM++: Improved Visual Explanations of CNN Decisions in Diabetic Retinopathy
  16. Chapter 7 ◾ Bangla Sign Language Recognition Using a Concatenated BdSL Network
  17. Chapter 8 ◾ ChestXRNet: A Multi-class Deep Convolutional Neural Network for Detecting Abnormalities in Chest X-Ray Images
  18. Chapter 9 ◾ Achieving Human Level Performance on the Original Omniglot Challenge
  19. Chapter 10 ◾ A Real-Time Classification Model for Bengali Character Recognition in Air-Writing
  20. Chapter 11 ◾ A Deep Learning Approach for Covid-19 Detection in Chest X-Rays
  21. Chapter 12 ◾ Automatic Image Captioning Using Deep Learning
  22. Chapter 13 ◾ A Convolutional Neural Network Based Approach to Recognize Bangla Handwritten Characters
  23. Chapter 14 ◾ Flood Region Detection Based on K-Means Algorithm and Color Probability
  24. Chapter 15 ◾ Fabrication of Smart Eye Controlled Wheelchair for Disabled Person
  25. Index