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Introduction to Artificial Intelligence and Biometrics Applications
| Content Provider | Scilit |
|---|---|
| Author | Waymond, Rodgers |
| Copyright Year | 2020 |
| Description | Artificial Intelligence (AI) represents human intelligence exhibited by a machine. It is the ability of machines to inculcate the ability to think, to build perceptions, plan in advance and to respond like people. One of the many aims of AI is to develop problem-solving or decision-making skills in order to assist people with their daily chores efficiently and effectively. Machine learning is a subset of AI since the decisive goal is to make machines self-dependent, whereby it can make decisions based on logic, reasoning, rational thinking and past experiences. AI can also be defined as the area of computer science which deals with the approaches that computers can be made to perform cognitive functions attributed to people. Moreover, AI draws from the fields of computer science, cognitive science, engineering, ethics, linguistics, logic, mathematics, natural sciences, philosophy, psychology, and statistics. Deep Learning has led the way in revolutionizing analytics and enabling practical applications of AI. The Throughput Model (see Figure 1.2) depicts information processed by people thinking processes or AI by combining machine learning, neural networks, algorithms, and deep learning. The Throughput Model is partially based upon a conceptual framework of decision-making. Book Name: Artificial Intelligence in a Throughput Model |
| Related Links | https://content.taylorfrancis.com/books/download?dac=C2018-0-96835-7&isbn=9780429266065&doi=10.1201/9780429266065-1&format=pdf |
| DOI | 10.1201/9780429266065-1 |
| Language | English |
| Publisher | Informa UK Limited |
| Publisher Date | 2020-03-06 |
| Access Restriction | Open |
| Subject Keyword | Book Name: Artificial Intelligence in a Throughput Model Information Systems Decision Making Intelligence |
| Content Type | Text |
| Resource Type | Chapter |