As the cornerstone voice of the development of artificial intelligence, data annotation is an important link in the development of artificial intelligence. Audio or speech recorded in any format can be understood by machines through machine learning. NLP-based speech recognition models require annotated audio so that applications such as chatbots or smart devices can understand the … Read more
The goal of NLP natural language processing is to train machines to understand or generate human language, but it is easier said than done, and NLP is also one of the most difficult problems in the field of artificial intelligence. What does NLP annotation mean? NLP is a branch of artificial intelligence that enables machines … Read more
We envision a computer future in which machines and humans interact in a symbiotic manner, and to accomplish this requires the power of computer vision and data annotation . Machines can now analyze and process human facial appearance to determine our emotions in real time, an area where advances are entirely attributable to the field of computer … Read more
Data labeling is the cornerstone of the artificial intelligence industry. The mainstream training mode of artificial intelligence is “question-sea tactics”, let artificial intelligence do enough questions, and then use the answers to tell it right or wrong. Therefore, machine learning needs to be supported by a large amount of effective data, and these data need to … Read more
The purpose of data annotation semantic is to tell the machine which things belong to which category or have certain attributes in supervised learning. segmentation annotation is actually a pixel-level classification, which predicts which object the target pixel belongs to. So the purpose of labeling is to tell the machine which pixels belong to which … Read more
In recent years, pictures machine learning techniques centered on deep learning have attracted attention. For example, self-driving cars have gradually become possible, but in the entire deep learning process, algorithms are required to recognize and learn images provided as raw data. In this process, semantic segmentation technology is applied. So, how does semantic segmentation annotate pictures? Let’s … Read more
Self-driving automatic car companies hope to collect a large amount of data, which can provide more useful references for autonomous driving. This data set has two main parts: 1. Collect data through various means such as vehicle detection, lane change, road traffic sign recognition, pedestrian and bicycle detection; 2. Data annotation through visual recognition. Challenges … Read more
As one of the mainstream methods of voice human-computer interaction, voice has unique advantages and charms. A seemingly short piece of voice not only contains the text content that the speaker wants to convey, but also contains the speaker’s identity, language category, speaker’s emotional state, the environment in which they speak, etc. What is Voice … Read more
Natural language text dialogue is one of the main challenges in the semantic understanding of network big data, known as the jewel in the crown of artificial intelligence, and text data annotation is the most basic and important link in this series of work. So, what is text annotation? What are the labeling methods? Let’s introduce it … Read more
The perception algorithm based on 3D point cloud data is the core technology path of some autonomous driving companies, and has created a large-scale demand for 3D point cloud data labeling. So, what is 3D point cloud annotation? What are the methods for 3D point cloud annotation? Let’s introduce it below. What is 3D point cloud annotation? The … Read more