Optical character recognition, Optical character reader or OCR is the process of reading printed or handwritten text and converting them into machine-encoded text. OCR is mainly used in the field of artificial intelligence, pattern recognition, and computer vision.
So how does it work? In simple words, for a computer, an image is nothing but a collection of pixels. In OCR processing, the image is scanned for light and dark areas to identify each character. Continue reading
Many startups would like to incorporate a machine learning component into their product(s). Most of these products are unique in terms of the business, the data that is required to train the machine learning models, and the data that can be collected. One of the main challenges that these startups have is the availability of data specific to their business problem. Unfortunately, the quality of the machine learning algorithms is dependent on the quality of the domain specific data that is used to train these models. Generic data sets are not useful for the unique problems that these startups are solving. As a result, they cannot rollout a feature involving machine learning until they can collect enough data. On the other hand, customers ask for the product feature before their usage can generate the required data. In such a situation, one needs to rollout a machine learning solution incrementally. For this to happen, there must be a synergy between the data and the algorithms that have the ability to process this data. To enforce this synergy, we propose a computational model that we refer to as “Data Fingerprinting”. Continue reading
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