Simply put, semantic segmentation is to assign each pixel in an image to a category in order 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 region. The self-developed data annotation platform covers most mainstream annotation tools, which is simple, convenient and efficient. The image labeling workbench is equipped with rich intelligent auxiliary labeling functions to improve labeling efficiency. The platform supports the automatic recognition of the object type of the current picture, automatically adding category labels to the recognition results, and classifying or sorting the features; Intelligent AI semantic segmentation model supporting artificial point filling can quickly complete the classification and labeling of object areas in pixel-level image categories; Support automatic marking of picture object content. In addition, the 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 data labeling platform, Jinglianwen Technology attaches importance to task collaboration, and can accurately transfer control from task creation, task assignment and labeling to quality inspection/sampling inspection, thus realizing the whole process control of data labeling process. After the data is marked, the accuracy of the data is guaranteed through different links such as audit, quality inspection and acceptance, and professionals control the quality and time nodes of data marking in each link, and the upstream and downstream work links are perfectly connected, which can improve efficiency on the premise of ensuring 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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