Sign Language Translator from Video to Speech - 2019

The goal of this project was to recognize the sign Language from video and generate simple English sentences.

  • Created the sign language data set for 30 sign words and 24 alphabets which could be classified using just one image frame.
  • Developed a deep learning model for classifying sign language images to corresponding sign words by transfer learning of the Inception V3 architecture and extended it to videos for generating simple English sentences
  • Got an accuracy of 62.5% on the test set under normal lighting conditions.
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Customized Adversarial Image Generator - 2018

The goal of this project was to implement fast and efficient Customized Adversarial Image Generator which can generate adversarial images for MNIST dataset.

  • The User has the option to specify the input image and the target class, the perturbed input image which will be classified as target class will be produced.
  • Implemented a variation of Fast Gradient Sign Method (FGSM) algorithm to perturb the input image.
  • The Perturbed image which will be indistinguishable to input image by Human eye are produced.
  • Reference : Explaining and Harnessing Adversarial Examples by Ian J. Goodfellow et al.
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Credit Card Fraud Detection - 2018

The goal of this project was to predict whether a given credit card transaction is fradulent or not using anomaly detection algorithm.

  • Used multivariate gaussian distribution to model the probability density function, which is then used to flag whether a transaction is fradulent or not.
  • Used Feature engineering to remove the features that didn't have much impact in modeling the density function.
  • Dataset source: Kaggle (
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ROOT-TMVA (Toolkit for Multivariate Analysis) - 2018

The goal of this project is to implement the new deep learning optimization algorithms in the ROOT-TMVA Project.

  • Refactored the existing code to include support for new deep learning optimization algorithms.
  • Implementing the optimization algorithms like SGD, RMSProp, Adam etc.
  • Unit tests and Integration tests are written to check the optimization algorithms.
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Docdroid - 2017

The goal of this project was to develop an android application that can help people in medical emergency situations like a heart attack or an accident.

  • Created an Android application that can be used by anyone during potential medical emergencies or accidents.
  • With a single tap, an ambulance will be automatically booked and the nearest hospital having adequate facility will be allocated to the patient.
  • Patient’s emergency contacts will receive notification about him and they can live track him, the status of ambulance etc.
  • The server side of the application is build using Flask framework.
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Online Assessment System for College Students - 2017

The goal of this project was to develop an Online Assessment System for college students.

  • Created an web application using Flask and Bootstrap framework.
  • Faculty can create their own tests and students can take them online.
  • It automatically evaluates both objective and descriptive answers and send the results to both student and faculty.
  • Faculty can view the list of students who have taken the test along with the marks obtained.
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Alpha Math Tools - 2015

The goal of this project was to develop an Android application for doing basic math.

  • The app was created using Java and XML.
  • It provides facilities for calculating interests for automobile/home loans.
  • It also provides facilities for school students to solve linear, quadratic equations, etc.
  • It is available on Play Store as “Alpha Math Tools” (Rating : 4.9 , Downloads: 100+ )
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