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
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
Data is the cornerstone of machine learning, without data, there is no model. Three types of data commonly used in the field of artificial intelligence: text, image and speech. Data collection refers to the process of collecting specific raw data of the target field and scene. The collected data is mainly unstructured data such as images, texts, voices, … Read more
3D label point cloud data annotation includes: feature extraction, 3D reconstruction and matching, and point cloud model extraction. Feature extraction: It refers to measuring the target surface or internal point cloud, obtaining the target surface or internal data, and comparing it with the original point cloud to determine whether there is similarity between the points. Three-dimensional … Read more
We often see “point cloud” marks on 3D models. In fact, many people don’t know that there is actually a very important point in 3D space—that is, some objects that we cannot see with the naked eye correspond to these feature points. (such as faces, hand shapes, objects, etc. that cannot be recognized by the … Read more
Artificial intelligence data sets refer to the data sets used to process and train AI models. Currently, the most used data sets in machine learning are: 1. Face image: face detection and feature extraction (including face recognition, gender distinction, age classification, etc.). 2. Speech Artificial recognition, language processing (natural language processing and speech recognition). 3. Video … Read more
Autonomous driving is a challenging technology, the success of which depends on a number of technical factors and experience in this field of technology. Data labeling is an important part of the automatic driving training process, and it is the key to changing the automatic driving technology. Why does autonomous driving need data labeling? Data labeling … Read more
Data annotation is the process of labeling data in various formats to enable machines to understand and process it accurately. Annotated data is an integral part of many machine learning and artificial intelligence applications. At the same time, it is one of the most time-consuming and labor-intensive parts of an ML project, and data annotation is … Read more
You’ve collected a lot of raw data, and now you want to feed that data into artificial intelligence (AI) systems so they can perform human-like activities. The problem is that these machines can only operate according to the parameters you define for your dataset. The way to bridge the gap between sample data and AI/ML is data … Read more
24x7offshoring is the one-stop solution for multinational organizations all over the world, with experience in over 100 mediums to large scale projects across five continents.