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Full Description
Computer vision is an interdisciplinary scientific field that deals with how computers obtain, store, interpret and understand digital images or videos using artificial intelligence based on neural networks, machine learning and deep learning methodologies. They are used in countless applications such as image retrieval and classification, driving and transport monitoring, medical diagnostics and aerial monitoring.
Written by a team of international experts, this edited book covers the state-of-the-art of advanced research in the fields of computer vision and recognition systems from fundamental concepts to methodologies and technologies and real world applications including object detection, biometrics, Deepfake detection, sentiment and emotion analysis, traffic enforcement camera monitoring, vehicle control and aerial remote sensing imagery.
The book will be useful for industry and academic researchers, scientists and engineers in the fields of computer vision, machine vision, image processing and recognition, multimedia, AI, machine and deep learning, data science, biometrics, security, and signal processing. It will also make a great course reference for advanced students and lecturers in these fields of research.
Contents
Chapter 1: Computer vision and recognition-based safe automated systems
Chapter 2: DLA: deep learning accelerator
Chapter 3: Intelligent image retrieval system using deep neural networks
Chapter 4: Handwritten digits recognition using dictionary learning
Chapter 5: Handwriting recognition using CNN and its optimization approach
Chapter 6: Real-time face mask detection on edge IoT devices
Chapter 7: Current challenges and applications of DeepFake systems
Chapter 8: Vehicle control system based on eye, iris, and gesture recognition with eye tracking
Chapter 9: Sentiment analysis using deep learning
Chapter 10: Classification of prefeature extracted images with deep convolutional neural network in facial emotion recognition of vehicle driver
Chapter 11: MobileNet architecture and its application to computer vision
Chapter 12: Study on traffic enforcement cameras monitoring to detect the wrong-way movement of vehicles using deep convolutional neural network
Chapter 13: Glasses for smart tourism applications
Chapter 14: Renal calculi detection using modified grey wolf optimization
Chapter 15: On multi-class aerial image classification using learning machines
Chapter 16: Machine learning methodology toward identification of mature citrus fruits
Chapter 17: Automated detection of defects and grading of cashew kernels using machine learning
