Artificial intelligence technology includes five major parts: computer vision, speech recognition, natural language processing, machine learning, and big data. Computer vision refers to using cameras and computers to replace human eyes to identify, track and measure targets, and further performs graphics processing to make computer processing into images that are more suitable for human eyes to observe or transmit to instruments for detection. Speech recognition technology is a high-tech technology that allows machines to convert speech signals into corresponding texts or commands through the process of recognition and understanding, etc.
Artificial intelligence technology includes five major parts: computer vision, speech recognition, natural language processing, machine learning, and big data.
1. Computer Vision
Computer vision refers to using cameras and computers instead of human eyes to identify, track and measure targets, and further perform graphics processing to make computer processing more suitable for human eyes. Images observed or transmitted to an instrument for detection.
As a scientific discipline, computer vision studies related theories and technologies, trying to build artificial intelligence systems that can obtain "information" from images or multi-dimensional data. Computer vision is still mainly in the stage of image information expression and object recognition, while artificial intelligence puts more emphasis on reasoning and decision-making. At present, computer vision is mainly used in security cameras, traffic cameras, unmanned driving, drones, finance, medical care, etc.
2. Speech recognition
Speech recognition technology is a high-tech technology that allows machines to convert speech signals into corresponding texts or commands through the process of recognition and understanding.
Speech recognition technology mainly includes three aspects: feature extraction technology, pattern matching criteria and model training technology. Speech recognition is the basis of human-computer interaction and mainly solves the problem of making machines understand what people say clearly. The most successful implementation of artificial intelligence at present is speech recognition technology. Speech recognition is currently mainly used in Internet of Vehicles, intelligent translation, smart homes, and autonomous driving.
3. Natural language processing
Natural language processing generally includes two parts: natural language understanding and natural language generation. Realizing natural language communication between humans and machines means that the computer can understand both natural language and natural language. The meaning of language text can also be used to express given intentions, thoughts, etc. in natural language text. The former is called natural language understanding, and the latter is called natural language generation. Natural language processing is an important direction in the fields of computer science and artificial intelligence.
For certain applications, practical systems with considerable natural language processing capabilities have emerged. Typical examples include: natural language interfaces for multilingual databases and expert systems, various machine translation systems, full-text information retrieval systems, automatic Abstract system, etc.
4. Machine Learning
Machine learning is to give machines the ability to learn like humans. It specializes in studying how computers can simulate or realize human learning behavior to acquire new knowledge or skills and reorganize The existing knowledge structure enables it to continuously improve its own performance, which is the core of artificial intelligence.
Machine learning has been widely used, such as: data mining, computer vision, natural language processing, biometric identification, search engines, medical diagnosis, stock market analysis, DNA sequence sequencing, speech and handwriting recognition , strategy games and robot applications.
5. Big Data
Big data, or huge amounts of data, refers to information that requires a new processing model to have stronger decision-making power, insight and process optimization capabilities. Massive, high-growth and diversified information assets. In other words, the ability to quickly obtain valuable information from various types of data is big data technology. Big data is the basis for the upgrade and evolution of AI intelligence. With big data, AI can continuously conduct simulation exercises and move closer to true artificial intelligence.
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