Here are a selection of projects that I have worked on in the domains of CV, CG, LLMs, GenAI, and ML/DL.
In this repo I implement basic 3D Computer Vision (3D CV), Graphics and 3D AI techniques for learning purpose.
This repo is a basic implementation of Diffusion Model to understand how diffusion works. This is the outcome of project course How Diffusion Models Work that I completed.
This Project is result of getting a hands-on experience of using different LLM models and tools. I am going to use a lot of tools and practice with small projects that will grow as I apply the new knowledge acquired. This repo is going to be a basic implementation of different LLMs to understand the finetuning, data preparation, evaluation & other techniques related to/of LLMs.
Investigating the performance of different deep learning models and their ensembles used for HAR in still images.
Developing simple ray tracing engine in C++.
In this notebook we will go over on how to train a object detection model on custom dataset using TensorFlow Object Detection API 2. For this purpose I used Oxford Pets dataset. We will monitor model training using TensorBoard.
This repo is simple implementation of Flappy Bird game using Unity and C# for learning purpose.
This project is aimed at covid19 detection using pretrained ResNet50 model.
This repo is simple demo of synthetic data creation using Blender and Python.
This chatbot helps the user throughout their journey of visiting a museum of the Roman Villa Nennig! We developed this chatbot using Google Cloud, Dialogflow Essentials and Telegram.
Objective of game is to help visitors of the Ludwig church, a historical church in Saarbrücken, explore the environment of the church in an entertaining way, we have created an AR-enabled painting app to be played inside the church. Players of this game need to walk to the different areas of the church while painting the surfaces. The app is developed using Unity and Vuforia engine.
This computer vision project is the pytorch implementations of UNet architecture for image segmenation on psacalVOC dataset to understand how CNNs are utilized for segmentation task.