Tensorflow video object recognition

The aim of this project was to prove that with live low quality video was possible to identify players of a particular team (or even diffrent teams). For this task the Tensorflow Image Recognition API were used, a custom training dataset were created and the process were runned in a GPU machine.

The next step ot this project is to get live video from a static camera and draw a player position heatmap.

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Electricity Fraud detection - LTSM Algorithm approach

A sophisticated approach to identify fraud electricity consumption from customers were developed. The consumption data from customers was used to train the LSTM algorithm. But this input data was sliced by season, by day, by month and even by hour in order identify several electricity use patterns. For this task different data sources were integrated with python data processing code, Tensorflow data analytics framework and Dash framework for dynamic visual representation.

The final result is an accurate and self explanatory graphical fraud detector tool with dynamic graphs.

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Python Dashboard data analytics

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Integration between postgreSQL, Python and Grafana for Data Analytics

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