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Full-Text Articles in Engineering
Voice Controlled Augmented Reality: A Comparison Of Speech-Recognition Tools For Ar Applications, Juan Estrella
Voice Controlled Augmented Reality: A Comparison Of Speech-Recognition Tools For Ar Applications, Juan Estrella
Publications and Research
Augmented Reality (AR) refers to the technologies that enhance the version of the physical environment with computer-generated sensory input such as sound and graphics overlaid on top of the user’s view of the real world. Artificial Intelligence (AI) studies how to make computer programs and machines "smart" and take decisions. Our research project focuses on exploring the Integration of AI in AR applications. Specifically, on using Speech Recognition or Natural Language Processing for controlling virtual AR objects and enhancing the human-computer interaction. It is obvious that integration of AI and AR is of great value. However, for developers, it is …
On Using Ai Bots For Voice Controlled Augmented Reality Applications, Juan Estrella
On Using Ai Bots For Voice Controlled Augmented Reality Applications, Juan Estrella
Publications and Research
Artificial Intelligence (AI) has the potential to benefit society in the realms of medicine, security, manufacturing, entertainment, marketing, and many others. One of the advances of AI is in the field of Natural Language Processing and Speech Recognition; making computers understand what humans say and mean. On the other hand, the term Augmented Reality (AR) refers to the technologies that superimpose digital content generated by computers over the user’s view of the real world. AR technologies enhance the version of the physical environment with computergenerated sensory input such as sound, video, or graphics overlaid on top of the real-world view. …
Scale Up Bayesian Network Learning, Xiannian Fan
Scale Up Bayesian Network Learning, Xiannian Fan
Dissertations, Theses, and Capstone Projects
Bayesian networks are widely used graphical models which represent uncertain relations between the random variables in a domain compactly and intuitively. The first step of applying Bayesian networks to real-word problems is typically building the network structure. Optimal structure learning via score-and-search has become an active research topic in recent years. In this context, a scoring function is used to measure the goodness of fit of a structure to given data, and the goal is to find the structure which optimizes the scoring function. The problem has been viewed as a shortest path problem, and has been shown to be …