What does semantic segmentation mean?

Semantic segmentation is a typical computer vision problem, which involves taking some original data (for example, plane images) as input and converting them into masks with highlighted regions of interest. Many people use the term full-pixel semantic segmentation, in which every pixel in an image is assigned to a category. ?

in short, semantic segmentation is to assign each pixel in an image to a category, so as to better understand the content in the image. This is very useful for many applications, such as self-driving cars, medical image analysis and robot vision.

Jinglianwen Technology is one of the largest AI basic data service providers in the Yangtze River Delta. The self-developed data annotation platform covers most mainstream annotation tools, which is simple, convenient and efficient to operate. The image labeling workbench is equipped with rich intelligent auxiliary labeling functions to improve labeling efficiency. The platform supports automatic recognition of the object type of the current picture, automatic addition of category labels to the recognition results, and feature classification or sorting; Support the intelligent AI semantic segmentation model with manual point filling, which can quickly complete the classification and labeling of object areas in pixel-level image categories; Support the automatic marking of the contents of picture objects. In addition, Jinglianwen data platform also has the ability of automatic target detection, which can quickly realize the tracking and positioning of the same target in the image after video frame extraction.

In the process management of the data labeling platform, Jinglianwen Technology attaches importance to job collaboration, which can accurately transfer control from task creation, task assignment and labeling to quality inspection/sampling inspection, and realize the whole process control of the data labeling process. After data labeling, it goes through different links such as audit, quality inspection and acceptance to ensure the accuracy of data, and every link has professionals to control the quality and time nodes of data labeling, so as to make a perfect connection between upstream and downstream work links, which can ensure the quality. In addition, Jinglianwen Technology follows the principle of separation of bidding and auditing, has a perfect risk management and control mechanism, and supports the privatization deployment of the platform, which can better improve the efficiency and accuracy of data labeling and ensure the privacy and security of data in all directions.

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