Comparison Analysis of Different Face Detection Techniques
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Comparison Analysis of Different Face Detection Techniques
Published and awarded at a reputed conference for excellence in research on Machine Learning and Neural Networks.
Neha Singh
Engineer. Consultant. Creative Marketer in the Making.
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Project Overview
- Conducted a detailed comparative study of traditional algorithms vs. deep learning methods for face detection.
- Analyzed techniques like Haar Cascades, HOG + SVM, and CNN-based models (e.g., MTCNN, YOLO).
- Evaluated performance using accuracy, speed, and robustness under varied lighting and angles.
- Implemented and tested models using Python, OpenCV, and TensorFlow.
- Published in IEEE and received the Best Paper Award for innovation and clarity of analysis.
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