Supervised Text Recognition Task
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A Supervised Text Recognition Task is a text recognition task that is a supervised string segmentation task and a supervised text-item classification task.
- Context:
- input: a Text Recognition Training Corpus.
- It can (typically) be supported by a Supervised Text Recognition System (that implements a supervised text recognition algorithm).
- It can (typically) require a significant amount of labeled data for effective training.
- It can (often) involve preprocessing steps such as image normalization, noise reduction, and feature extraction.
- ...
- Example(s):
- an Supervised OCR System trained to convert scanned documents into editable text.
- a Supervised Handwriting Recognition System that can interpret handwritten notes.
- a Supervised NER Task.
- ...
- Counter-Example(s):
- an Unsupervised Text Clustering Task, which does not rely on labeled data.
- a Text-to-Speech System, which is focused on converting text into spoken voice rather than recognizing text.
- See: Supervised NLP, Data Labeling, Pattern Recognition.