Background

Our team was tasked with developing two projects: one on detecting lymphocytes using Mask R-CNN and the other on developing a virtual mouse for an ICV project. These projects required a lot of hard work and problem-solving, but we were excited to take on the challenge.

Problem

The main challenge we faced was developing accurate models for both projects. For the lymphocyte detection project, we needed to train our model to accurately identify different types of lymphocytes in medical images. For the virtual mouse project, we needed to create a realistic simulation that could be used for research purposes.

Solution

To overcome these challenges, we utilized machine learning algorithms and deep learning techniques. For the lymphocyte detection project, we used Mask R-CNN to train our model on medical images. We also implemented data augmentation techniques to improve the accuracy of our model. For the virtual mouse project, we developed a simulation using Unity3D and programmed it with realistic movements and behaviors.

Impact

Successfully developed accurate models for both projects
Lymphocyte detection project: improved accuracy by X%
Virtual mouse project: received positive feedback from researchers who found it useful for their studies
Inspired team members to continue exploring machine learning and deep learning techniques in future projects

Team

Zeeshan Khan - Classmate
- Applied machine learning algorithms for AI project

Developed Accurate Models with Machine Learning