Jun - Jul 2023
Computer Vision Research Intern in the Optical Engineering team at Cognex where I investigated deep learning methods to expand the depth of field of machine vision cameras with big apertures.
2022 - Present
Awarded the Erasmus Mundus Joint Master's Degree scholarship to study in the Computational Colour and Spectral Imaging program at NTNU, Norway and UGR, Spain.
2021 - 2022
Associate Data Scientist in the AI team at i2c Inc. where I delivered computer vision based products like the automated cheque deposit service which uses computer vision and deep learning algorithms to read and parse handwritten information on bank cheques.
Projects
Identity Based Face Synthesis
Developed method to control extraction of specific data points from the latent space of GANs. Proposed CGAN + Autoencoder for generating IDs from faces and faces from corresponding IDs. Deployed model on Nvidia Jetson Nano and a Flask web app.Stack used: PyTorch, Nvidia CUDA, Flask, Arduino
Survey of Deep Learning Methods for Single Image Super Resolution
Literature review of deep learning methods to achieve single image super resolution. Identified the current state-of-the-art method. Developed taxonomy and compared performance. Identified approaches that deliver results. Proposed future areas of research and limitations of current methods
Semantic Appearance Manipulator
Image manipulation program using Mask R-CNN. Replaces detected objects in image with another image. Developed using PyTorch, Numpy, Matplotlib, and Pillow
Creation of Small Footprint FOGRA 39 CMYK ICC Profile
Developed a small footprint ICC profile creation method. Reduced size of Fogra 39 CMYK profile by 74%. Wrote Python script to automate small footprint profile creation. Wrote Python script to convert ICC profiles from v2 to v4.