ECG Arrhythmia Detection with ResNet and Transfer Learning
ResNet18 for Image Classification
This app uses a deep learning model built with PyTorch to detect diseases in plants based on images of their leaves. Currently, the app supports disease detection for maize (corn), but we plan to expand to more plants in the future.
PyTorch implementation of ResNet18 on CIFAR-10 dataset achieving 96.22%
A deep‑learning–based face detection and recognition pipeline built with facenet‑pytorch, combining MTCNN for face localization and InceptionResnetV1 for face embedding and identity matching. This project loads pre‑computed embeddings (embeddings.pt) and compares new faces against known identities using Euclidean distance.
AI-powered brain tumor detection from MRI scans using PyTorch and Streamlit with Grad-CAM visualizations
Dynamic Activation of Neural Network Blocks Based on Graph Representation for Energy-Efficient Inference
REST API based on PyTorch (ResNet18) for classifying 50 categories of natural and household sounds (rain, chainsaw, glass breaking, etc.) from audio files. Mel spectrograms + FastAPI. Val accuracy 86%. Trained in Google Colab on ESC-50.
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