Data annotation is the process of adding labels to raw data (such as images, videos, text, audio, and 3D point clouds). Data with labels is known as training data, and these labels form a representation of which class of objects the data belongs to, helping the machine learning model accurately identify what is in the data even when it encounters data it has never seen before in the future.?
Currently, the mainstream machine learning approach is dominated by supervised deep learning, which has a strong dependency on labeled data, and raw data that has not been labeled and processed is dominated by unstructured data, which is difficult for machines to identify and learn from. Only structured data after labeling can be used for algorithm model training.
The types of data annotation are mainly image annotation, speech annotation, 3D point cloud annotation and text annotation.
In the development of artificial intelligence, data has always been regarded as its "blood". Data annotation is a key part of the effective operation of artificial intelligence algorithms, and to realize artificial intelligence, we must first let the computer learn to understand and have the ability to judge things. The process of data labeling is to provide a large number of samples for the machine system to learn through artificial labeling, data labeling is the need for the machine to identify and distinguish the data labeling, and then allow the computer to continuously learn the characteristics of these data, and ultimately realize the computer can identify on its own.
Jinglian Technology, as a professional Al data labeling company, is committed to promoting the construction of data resource standard system, and providing high-quality data elements supply services from data production, data management platform, data assets market-oriented circulation, data resource planning and other aspects.
At present, it owns four large-scale data processing bases in Van, more than 1,000 professional artificial intelligence data trainers, develops a mature intelligent data labeling platform covering labeling workbench and capacity management system, and has obtained ISO9001 international quality management certification, ISO27001 international information security management certification, ISO27701 international privacy security It also obtained ISO9001 international quality management certification, ISO27001 international information security management certification, and ISO27701 international privacy security management certification, and provides complete voice, image, text, and video processing capabilities in all fields. It delivers high-quality AI data for algorithm models in smart driving, smart city, smart home, smart finance, smart education, smart security, new retail and other fields.
Successively won the "National High-tech Enterprise", Hangzhou "Blue Plan" enterprises, Hangzhou "Eagle Program" enterprises and other honors, at the same time, is the Internet financial At the same time, it is a member unit of the Internet Financial Authentication Alliance, a member of the Biometric Identification Sub-Committee of the National Information Standard Committee, a member of the Artificial Intelligence Sub-Committee of the National Information Standard Committee, a member of the Artificial Intelligence Industry Alliance of Zhejiang Province, and a member of the Industry Union of City Brain of Zhejiang Province. When carrying out data annotation, it is necessary to define the labeling methods and rules according to specific needs and to formulate the labeling specifications in order to ensure the quality and unity of the labeling. At the same time, you can also use artificial intelligence technology to assist in data labeling to improve efficiency and accuracy.
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