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The aim of this project was to design a program that can take an audio file as an input and give a description of where it was recorded as an output, by utilising a combination of machine learning techniques and convolution reverb. Mainly, I am interested in the forensic applications of this type of sound analysis system and the research conducted during this project, as well as the program itself, was explored from this perspective.
Akshar Prasad - Rashtreeya Vidyalaya College of Engineering (RVCE) Bangalore
Machine Learning Techniques to Understand Partial and Implied Data Values for the Conversion of Natural Language to SQL Queries on HPCC Systems (View larger image)
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Application of CNN models on the transactional data for identification of anomalies and fraud has proved to be quite promising as the model itself takes care of most of the static and dynamic feature extraction hence making the detection easier than random forests. In this project we aim to solve the problem outlined above by the application of CNN model in ML for dynamic detection of fraud in stored-value cards.
Sathvik K R - Rashtreeya Vidyalaya College of Engineering (RVCE) Bangalore
Octave Plugin for HPCC Systems (View larger image)
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