The issue of data labeling quality has been a major topic of concern in the AI/ML community. Perhaps the most common “principle” you’re likely to come across when solving this puzzle is “garbage in, garbage out”. By saying this, we want to emphasize the fundamental laws of training data for AI and ML development projects. Low-quality training … Read more
Why is data labeling so important in machine learning? There are many reasons why data labeling is important. Some of these include: 1. Without a large amount of data annotation, your program may fail. This is because your program cannot understand what each piece of data actually describes. In order for your program to execute correctly, it must know what … Read more
Data annotation for autonomous vehicles There Driving are multiple image annotation types such as polygons, bounding boxes, 3D cuboids, semantic segmentation, lines, and splines that can be incorporated into autonomous vehicles. The main goal of data annotation in automobiles is to classify and segment objects in images or videos. We’ve seen a lot of buzz about … Read more
In recent years, data labeling with the rapid development of artificial intelligence, intelligent driving , as an important part of strategic emerging industries, has attracted more and more attention. Intelligent driving technology refers to the technology that relies on machines to drive and completely replaces people in special cases. It mainly includes three links: network navigation, … Read more
Today, artificial intelligence labeling has long been common in our lives. Such as “face recognition” and “voice wake-up audio” all belong to the category of artificial intelligence. When it comes to artificial intelligence, we must talk about data annotation. Data annotation is to output “data” for artificial intelligence research that can be used for research. So, what … Read more
With the continuous collection emergence of diverse AI scenarios, related companies have more urgent needs for the collection and labeling of multi-scenario data in different fields, which has also led to an increasing demand for customized data collection and labeling in the market, especially in deep learning. domain, more data is needed to improve the … 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
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
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
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