Project using PyTorch in which we create custom datasets and dataloaders, train a convnext_tiny model and log it using tensorboard, do inferences and use Captum for more detailed results.
Mammographic images classification.
This repository contains my work on Alzheimer's Disease detection using deep learning models applied to neuroimaging data. The projects explore multiple architectures and datasets to classify Alzheimer's stages based on MRI scans.
Exploring the Application of Attention Mechanisms in Conjunction with Baseline Models on the COVID-19-CT Dataset
I built a web app for medical image analysis that allows users to upload images and receive classification results. The backend uses Spring Boot with PostgreSQL for authentication and role management, while FastAPI handles the image processing and making predictions. On the frontend, I developed a responsive ReactJS interface.
YOLO-style object detector implemented from scratch with a custom loss function, pre-trained feature extractor, and end-to-end training pipeline on PASCAL VOC for real-time object localization and classification. Tech: Python (pytorch, scikit-learn, numpy, matplotlib, tqdm, PIL)
Deep learning for ASD / Autism detection
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