IFB101 Lecture Notes - Lecture 10: Optical Character Recognition, Machine Vision, Block Chain
Document Summary
Letting machines think like machines (not trying to make them think people: greater and faster computational resources, taking a learning approach rather than a strictly rules-based approach, more data available for the machines to learn from. Focus on specific problems (e. g. manipulating a mobile device) Ai - helps us to decide and act. Senses - spoke about these with internet of things. Language processing: listening/reading words and turning them into ideas and relationships. Situation assessment: figuring out what is going on in the world. Learning: from examples or the analysis of data. Language generation: figuring out what to say and generating the language to say it. Speech: generating the audible sounds to communicate: robotic control: moving the different parts of your body or other artefacts to express yourself or create other actions. What is machine vision: application of computer vision to industry & manufacturing, machine vision is subfield of engineering that incorporates, computer science, optics, mechanical engineering.
