Labeling

1. What is Labeling?

Data labeling is a process of tagging labels to data samples to help the computer to correctly understand data needed for training. To enhance the accuracy of model training, data that exist in the form of images, videos, and texts needs to be labeled to prepare an appropriate train set. For accurate learning of artificial intelligence, data that exist in the form of images, text, etc. needs to be classified by labeling them accordingly. Because the model analyzes and predicts results based on labeled data, the accuracy and consistency of the labeling process is important. This task requires a significant time and effort because due to the manual labeling operations, but the recent labeling aids offer easier and simpler work process.

2. Labeling Examples

Data labeling is an essential process in image classification and object recognition models that require image data sets. To label image data, you need to find an object to classify in the image, designate the object area, and tag a label.

To label 'fire' in the image above, find and mark the area of fire with a label. If successfully labeled images like the one above are feeded into the model for training, the model will analyze the area labeled for 'fire' and automatically find a pattern to locate fire from other images as well.

3. Labeling with CLICK AI

Click AI offers a labeling aid service for image classification or object detection to make the process simpler for users. Bounding boxes and polygon features allow you to successfully tag labels in detail, and you can directly upload the labeled data to you model as train sets.

You can access Click AI's labeling tool from the object detection labeling tab on our web. More information about our labeling tool services is available at 🏈물체인식 라벨링.

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