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This book is a comprehensive curation, exposition and illustrative discussion of recent research tools for interpretability of deep learning models, with a focus on neural network architectures. In addition, it includes several case studies from application-oriented articles in the fields of computer vision, optics and machine learning related topic. The book can be used as a monograph on interpretability in deep learning covering the most recent topics as well as a textbook for graduate students. Scientists with research, development and application responsibilities benefit from its systematic exposition. .

Artificial intelligence. --- Operations research. --- Knowledge management. --- Computer vision. --- Artificial Intelligence. --- Operations Research and Decision Theory. --- Knowledge Management. --- Computer Vision. --- Machine vision --- Vision, Computer --- Artificial intelligence --- Image processing --- Pattern recognition systems --- Management of knowledge assets --- Management --- Information technology --- Intellectual capital --- Organizational learning --- Operational analysis --- Operational research --- Industrial engineering --- Management science --- Research --- System theory --- AI (Artificial intelligence) --- Artificial thinking --- Electronic brains --- Intellectronics --- Intelligence, Artificial --- Intelligent machines --- Machine intelligence --- Thinking, Artificial --- Bionics --- Cognitive science --- Digital computer simulation --- Electronic data processing --- Logic machines --- Machine theory --- Self-organizing systems --- Simulation methods --- Fifth generation computers --- Neural computers --- Deep learning (Machine learning) --- Learning, Deep (Machine learning) --- Iterative methods (Mathematics) --- Machine learning

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

This book is a comprehensive curation, exposition and illustrative discussion of recent research tools for interpretability of deep learning models, with a focus on neural network architectures. In addition, it includes several case studies from application-oriented articles in the fields of computer vision, optics and machine learning related topic. The book can be used as a monograph on interpretability in deep learning covering the most recent topics as well as a textbook for graduate students. Scientists with research, development and application responsibilities benefit from its systematic exposition. .

Theory of knowledge --- Operational research. Game theory --- Mathematical statistics --- Planning (firm) --- Artificial intelligence. Robotics. Simulation. Graphics --- Computer. Automation --- computervisie --- kennismanagement --- mathematische modellen --- econometrie --- KI (kunstmatige intelligentie) --- operationeel onderzoek --- Deep learning (Machine learning)