<p>Are you a computer scientist working on image analysis? Are you a biologist seeking tools to process the microscopy data from image-based experiments? <i>Computer Vision for Microscopy Image Analysis</i> provides a comprehensive and in-depth discussion of modern computer vision techniques, in par
Computer Vision and Image Analysis for Industry 4.0
โ Scribed by Nazmul Siddique, Mohammad Shamsul Arefin, Md Atiqur Rahman Ahad, M. Ali Akber Dewan
- Publisher
- CRC Press/Chapman & Hall
- Year
- 2023
- Tongue
- English
- Leaves
- 214
- Category
- Library
No coin nor oath required. For personal study only.
โฆ Synopsis
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.
โฆ Table of Contents
Cover
Half Title
Title Page
Copyright Page
Dedication
Contents
Preface
Contributors
Editors
CHAPTER 1: BN-HTRd: A Benchmark Dataset for Document Level Offline Bangla Handwritten Text Recognition (HTR) and Line Segmentation
CHAPTER 2: A New Approach Using a Convolutional Neural Network for Crop and Weed Classification
CHAPTER 3: Lemon Fruit Detection and Instance Segmentation in an Orchard Environment Using Mask R-CNN and YOLOv5
CHAPTER 4: A Deep Learning Approach in Detailed Fingerprint Identification
CHAPTER 5: Probing Skin Lesions and Performing Classification of Skin Cancer Using EfficientNet while Resolving Class Imbalance Using SMOTE
CHAPTER 6: Advanced GradCAM++: Improved Visual Explanations of CNN Decisions in Diabetic Retinopathy
CHAPTER 7: Bangla Sign Language Recognition Using a Concatenated BdSL Network
CHAPTER 8: ChestXRNet: A Multi-class Deep Convolutional Neural Network for Detecting Abnormalities in Chest X-Ray Images
CHAPTER 9: Achieving Human Level Performance on the Original Omniglot Challenge
CHAPTER 10: A Real-Time Classification Model for Bengali Character Recognition in Air-Writing
CHAPTER 11: A Deep Learning Approach for Covid-19 Detection in Chest X-Rays
CHAPTER 12: Automatic Image Captioning Using Deep Learning
CHAPTER 13: A Convolutional Neural Network-based Approach to Recognize Bangla Handwritten Characters
CHAPTER 14: Flood Region Detection Based on K-Means Algorithm and Color Probability
CHAPTER 15: Fabrication of Smart Eye Controlled Wheelchair for Disabled Person
Index
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