Semi-Supervised Learning

Image classification is the most common computer vision problem where an algorithm process an image and classifies the classes. This technique extended with object detection algorithms, where it uses localization with the classification. In object detection methods object is localized by a bounding box, where the bounding box is represented by four value points according to the pixels in an image. If you are trying to train an object detection model with custom data, human resources are required to annotate enormous amounts of data manually. Consider a large amount of image data set that need to train on a model, and manually labeling all of this data ourselves may take a long time and logistically difficult.