Project

Comparison Analysis of Different Face Detection Techniques

Published and awarded at a reputed conference for excellence in research on Machine Learning and Neural Networks.
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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.

About the Creator

Neha Singh

Neha Singh

Engineer. Consultant. Creative Marketer in the Making.
SQL Team Management Instagram Marketing Cross-functional Collaboration Workforce Planning Storytelling Marketing Analytics CRM Integration
Joined: May 2025

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