Intelligent Systems and Applications in Computer Vision

Nitin Mittal, Amit Kant Pandit, Mohamed Abouhawwash, Shubham Mahajan, Nitin Mittal, Amit Kant Pandit, Mohamed Abouhawwash, Shubham Mahajan

• Publisher: CRC Press
• Year: 2023
• Print ISBN: 9781032392950
• eBook ISBN: 9781000985863
• Topic: Computer Science
• Subtopic: Computer Engineering
• Index: Computer Science

The book comprehensively covers a wide range of evolutionary computer vision methods and applications, feature selection and extraction for training and classification, and metaheuristic algorithms in image processing. It further discusses optimized image segmentation, its analysis, pattern recognition, and object detection.

Features:

• Discusses machine learning-based analytics such as GAN networks, autoencoders, computational imaging, and quantum computing
• Covers deep learning algorithms in computer vision
• Showcases novel solutions such as multi-resolution analysis in imaging processing, and metaheuristic algorithms for tackling challenges associated with image processing
• Highlight optimization problems such as image segmentation and minimized feature design vector
• Presents platform and simulation tools for image processing and segmentation

The book aims to get the readers familiar with the fundamentals of computational intelligence as well as the recent advancements in related technologies like smart applications of digital images, and other enabling technologies from the context of image processing and computer vision. It further covers important topics such as image watermarking, steganography, morphological processing, and optimized image segmentation. It will serve as an ideal reference text for senior undergraduate, graduate students, and academic researchers in fields including electrical engineering, electronics, communications engineering, and computer engineering.

Table of contents

• Cover
• Half Title
• Title Page
• Copyright Page
• Table of Contents
• About the editors
• List of Contributors
• Chapter 1 A review approach on deep learning algorithms in computer vision
• Chapter 2 Object extraction from real time color images using edge based approach
• Chapter 3 Deep learning techniques for image captioning
• Chapter 4 Deep learning-based object detection for computer vision tasks: A survey of methods and applications
• Chapter 5 Deep learning algorithms for computer vision: A deep insight into principles and applications
• Chapter 6 Handwritten equation solver using Convolutional Neural Network
• Chapter 7 Agriware: Crop suggester system by estimating the soil nutrient indicators
• Chapter 8 A machine learning based expeditious Covid-19 prediction model through clinical blood investigations
• Chapter 9 Comparison of image based and audio based techniques for bird species identification
• Chapter 10 Detection of Ichthyosis Vulgaris using SVM
• Chapter 11 Chest X-Ray diagnosis and report generation: Deep learning approach
• Chapter 12 Deep learning based automatic image caption generation for visually impaired people
• Chapter 13 Empirical analysis of machine learning techniques under class imbalance and incomplete datasets
• Chapter 14 Gabor filter as feature extractor in anomaly detection from radiology images
• Chapter 15 Discriminative features selection from Zernike moments for shape based image retrieval system
• Chapter 16 Corrected components of Zernike Moments for improved content based image retrieval: A comprehensive study
• Chapter 17 Translate and recreate text in an image
• Chapter 18 Multi-label Indian scene text language identification: Benchmark dataset and deep ensemble baseline
• Chapter 19 AI based wearables for healthcare applications: A survey of smart watches
• Chapter 20 Nature inspired computing for optimization
• Chapter 21 Automated smart billing cart for fruits
• Index