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Data digitalization
•Built Classification Model to convert the data from handwritten text to digitalized data for
•Implementation has placed conversion tool in its data entry process to ensure fast conversion rate
•Used techniques like Convolution neural network, opencv(contour-detection) , deployment in flask
•This approach helped the company to achieve 2 times faster conversion rate
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Identification of business opportunities in different region/area using luminosity
•Built an application to identify the business opportunity in each region/area using the region’s luminosity and map it with the current business in that region
•Techniques used : Computer vision , Image segmentation Models, Deep learning models (Regional Convolutional neural networks) , Algorithm Deployment in Flask
•This approach helped the company to replace traditional survey methods in identifying the business potential in specific area and application does the job with 90% accuracy
Continuous tracking of human body to prevent paralysing
•Built an application to alert the admin/nurse when no movement in patient is detected
•Techniques used : Computer Vision, Object tracking(Deep-sort), Deployment in Flask
• This helped the hospital to replace manual effort (24/7 surveillance by nurses) with algorithmic alerts with a 100% accuracy
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Suspicious Content detection
•Built a One Click Offline Application for Revenue Department – India to help them in identifying fraudulent money activity with 96% accuracy
•Techniques used : Computer vision , Image Classification Models, Deep learning models (Convolutional neural networks) , Algorithm Deployment in Flask
•This approach helped the department to replace the manual effort in identifying the suspicious activity. The application does the job in 20% of the manual time