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Today we’re joined by Cha Zhang, a Partner Engineering Manager at Microsoft Cloud & AI.
Cha’s work at MSFT is focused on exploring ways that new technologies can be applied to optical character recognition, or OCR, pushing the boundaries of what has been seen as an otherwise ‘solved’ problem. In our conversation with Cha, we explore some of the traditional challenges of doing OCR in the wild, and what are the ways in which deep learning algorithms are being applied to transform these solutions.
We also discuss the difficulties of using an end to end pipeline for OCR work, if there is a semi-supervised framing that could be used for OCR, the role of techniques like neural architecture search, how advances in NLP could influence the advancement of OCR problems, and much more.
The complete show notes for this episode can be found at twimlai.com/go/416.
By Sam Charrington4.7
419419 ratings
Today we’re joined by Cha Zhang, a Partner Engineering Manager at Microsoft Cloud & AI.
Cha’s work at MSFT is focused on exploring ways that new technologies can be applied to optical character recognition, or OCR, pushing the boundaries of what has been seen as an otherwise ‘solved’ problem. In our conversation with Cha, we explore some of the traditional challenges of doing OCR in the wild, and what are the ways in which deep learning algorithms are being applied to transform these solutions.
We also discuss the difficulties of using an end to end pipeline for OCR work, if there is a semi-supervised framing that could be used for OCR, the role of techniques like neural architecture search, how advances in NLP could influence the advancement of OCR problems, and much more.
The complete show notes for this episode can be found at twimlai.com/go/416.

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