After completing my master's program in Computer Science, I worked for about five years as a product manager, system analyst, and web programmer. Due to these experiences, I gained a good understanding of the entire software product's life cycle as a software engineer.
I have concentrated on learning and researching Computer Vision and Machine Learning for the last five years, contributing to a few research projects. As a result, my colleagues and I published seven research papers.
My research projects focused on:
- Residual-based texture classification using classical Machine Learning.
- Classification of texture images based on their unique image statistical properties using Classical Machine Learning and Deep Learning approaches.
- Effect of media compression on texture classification.
I got good experience using modern Machine Learning methods, and classical computer vision approaches to solve challenging problems in computer vision. Also, I gained good confidence in using Python, Keras 2.X, Tensorflow 2, OpenCV-python, Scikit-learn, Scikit-image. Apart from skills and knowledge, I am cordially enthusiastic to devote my professional career where I can be involved in solutions that combine modern machine learning approaches with Computer Vision systems.
I am always open to work on a new research topic. If you know python and also familiar with computer vision please email me.
Recent Work:
New Paper: Using CNNs to Identify the Origin of Finger Vein Image (preprint arXiv)
IEEE International Workshop on Biometrics and Forensics (IWBF) 2021 , Rome, Italy.
View my:
React
Typescript
Django
Laravel
Facebook
Microsoft
Google
Alibaba
D3
Tencent