Optical character recognition, or OCR for short, is used to describe algorithms and techniques (both electronic and mechanical) to convert images of text to machine-encoded text. Today on the show, Ahmad Anis shares how he applies Machine Learning to OCR for small hardware applications, for example, blurring a face in a video in real time or on a stream to safeguard privacy using AI. The panel also discusses various strategies related to learning and soft skills needed for success within the industry.
In this episode…
- Optical character recognition (OCR) defined
- Multiprocessing vs. multithreading
- I/O bound tasks vs. CPU tasks
- How to handle a retry in Python
- Strategies for employing on small hardware
- Template matching and preprocessing
- Gray scaling integrations
- How to learn and get started within the industry
- Reducing the scope and industry soft skills
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