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.

• 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