Weakly Supervised Learning
Weakly supervised learning is a machine learning framework where the model is trained using examples that are only partially annotated or labeled.
Most modern computer vision system involves models learned from human-labeled image examples. For instance, an object detector is typically trained on a large collection of images manually annotated with masks or bounding boxes denoting the location of the object of interest in each photo. The reliance on time-consuming human labeling poses a significant limitation to the practical application of these methods. Weakly supervised learning is aimed at reducing the amount of human intervention needed to train the models by making use of examples that are only partially labeled.
Semisupervised learninginvolves training a model using a...
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