- 🧠 Developed a CNN-based deep learning model to assist early autism detection through facial emotion recognition
- ⚙️ Built using Python, TensorFlow, and OpenCV
- 📊 Achieved 80% accuracy with optimized training and hyperparameter tuning
- 🔄 Implemented full pipeline: preprocessing → feature extraction → model evaluation
- 🚗 Designed a real-time fatigue detection system using eye-blink and head movement analysis
- 🧠 Built with OpenCV and CNN for continuous driver monitoring
- ⚡ Deployed lightweight model on edge device for low-latency inference
- 🚨 Integrated alert system to warn drivers upon detecting fatigue
- 📦 Developed YOLO-based object detection and counting system for live video streams
- 🎯 Implemented tracking algorithm to avoid duplicate counting
- ⚙️ Optimized for real-time performance and improved detection accuracy
- 🎥 Processed live video using OpenCV for efficient object tracking
-
🔭 I’m currently working on Computer Vision & Deep Learning projects (YOLO, CNN)
-
🌱 I’m currently learning Machine Learning and Edge AI deployment
-
👯 I’m looking to collaborate on AI/ML and IoT-based projects
-
🤔 I’m looking for help with model optimization and real-world deployment
-
💬 Ask me about Python, OpenCV, Flask, and Data Analysis
-
😄 Pronouns: She/Her
-
⚡ Fun fact: I enjoy building real-time AI systems that solve practical problems 🚀