My Projects

Developed a CNN and transfer learning-based framework for automated rice variety classification and disease detection. Evaluated 15 deep learning models, with EfficientNetB0 achieving the best performance. The work enhances agricultural automation and supports sustainable farming through AI-driven crop monitoring.

IoT-based home automation system for controlling lights, temperature, and other home appliances using Arduino.

Constructed a helmet detection system utilizing the YOLO model, resulting in precise detection in images, thereby improving workplace safety compliance. Trained on a dataset specifically created for recognizing safety helmets in different situations.

Developed a classifier to determine if a dragon fruit is mature or immature in images, using transfer learning with PyTorch. Leveraged a pre-trained model to achieve high accuracy on a custom dataset, effectively distinguishing between maturity stages in various conditions.

Developed an automated image organization system using facial recognition technology to streamline photo retrieval. By leveraging Python, OpenCV, and face recognition libraries, it matches user-provided photos with a large image repository, segregating and emailing relevant images.