Subhas Chandra Mukhopadhyay

Krishanthi P. Jayasundera

Boby George

Nagender Kumar Suryadevara

This book gathers the latest advances, innovations, and applications in the field of sensing technology, as presented by international researchers and engineers at the 15th International Conference on Sensing Technology (ICST), held in Sydney, Australia on December 5–7, 2022. Contributions include a wide range of topics such as: vision sensing, sensor signal processing, sensors phenomena and modelling, sensor characterization, smart sensors and sensor fusion, electromagnetic, chemical and physical sensors, electronic nose technology, biosensors, nano sensors, wireless sensors and WSN, Internet of Things, optical sensors, sensor arrays, intelligent sensing, Internet-based and remote data acquisition. The contributions, which were selected by means of a rigorous international peer-review process, present a wealth of exciting ideas that will open novel research directions and foster multidisciplinary collaboration among different specialists.

Proceedings of ICST'15

Sensing Technology

Pradeep Kumar Singh

Bijaya Ketan Panigrahi

Sudhir Kumar Sharma

Amit Prakash Singh

This book presents high-quality, original contributions (both theoretical and experimental) on Information Security, Machine Learning, Data Mining and Internet of Things (IoT). It gathers papers presented at ICETIT 2019, the 1st International Conference on Emerging Trends in Information Technology, which was held in Delhi, India, in June 2019. This conference series represents a targeted response to the growing need for research that reports on and assesses the practical implications of IoT and network technologies, AI and machine learning, data analytics and cloud computing, security and privacy, and next generation computing technologies.

Emerging Trends in Information Technology

Proceedings of ICETIT 2019

Apply Artificial Intelligence techniques in the browser or on resource constrained computing devices. Machine learning (ML) can be an intimidating subject until you know the essentials and for what applications it works. This book takes advantage of the intricacies of the ML processes by using a simple, flexible and portable programming language such as JavaScript to work with more approachable, fundamental coding ideas. Using JavaScript programming features along with standard libraries, you'll first learn to design and develop interactive graphics applications. Then move further into neural systems and human pose estimation strategies. For training and deploying your ML models in the browser, TensorFlow.js libraries will be emphasized. After conquering the fundamentals, you'll dig into the wilderness of ML. Employ the ML and Processing (P5) libraries for Human Gait analysis. Building up Gait recognition with themes, you'll come to understand a variety of ML implementation issues. For example, you’ll learn about the classification of normal and abnormal Gait patterns. With Beginning Machine Learning in the Browser, you’ll be on your way to becoming an experienced Machine Learning developer. What You’ll Learn Work with ML models, calculations, and information gathering Implement TensorFlow.js libraries for ML models Perform Human Gait Analysis using ML techniques in the browser Who This Book Is For Computer science students and research scholars, and novice programmers/web developers in the domain of Internet Technologies

Quick-start Guide to Gait Analysis with JavaScript and TensorFlow.js

Beginning Machine Learning in the Browser

Nagender Kumar Suryadevara

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