SafeGuard-CV is a real-time computer vision system that detects missing PPE (helmets) on construction sites using a fine-tuned YOLOv8s model, optimized for edge deployment via ONNX FP16 quantization.
A comprehensive comparative study of 10+ feature selection techniques (including RFE and SHAP) to optimize ML models. Achieved a 73% reduction in feature space while maintaining >96% accuracy, highlighting key trade-offs between performance efficiency and model interpretability for production environments.
🔹 Hands-on experience in building and training ML & DL models using TensorFlow 🤖 🔹 Skilled with Keras API, Tensors, & Computational Graphs ⚙️ 🔹 Developed projects like Image Classification & Neural Networks 🧠 🔹 Strong understanding of data preprocessing model evaluation 🔹 Exploring model
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