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Published at November 12

An Explainable Machine Learning Approach for Age and Gender Estimation in Living Individuals Using Dental Biometrics

cs.CV

cs.AI

Released Date: November 12, 2024

Authors: Mohsin Ali¹, Haider Raza¹, John Q Gan¹, Ariel Pokhojaev², Matanel Katz², Esra Kosan³, Dian Agustin Wahjuningrum⁴, Omnina Saleh⁵, Rachel Sarig², Akhilanada Chaurasia⁶

Aff.: ¹University of Essex, UK; ²Tel Aviv University, Israel; ³Oral Medicine and Oral Surgery, Germany; ⁴Universitas Airlangga, Indonesia; ⁵Boston University Henry M.Goldman, USA; ⁶King George's Medical University Lucknow, India

Arxiv: http://arxiv.org/abs/2411.08195v1

Gender Classification
SNo.	Model	F1	AUC
1	CatBoost Classifier	70.34	71.3
2	Gradient Boosting Classifier	69.88	69.8
3	Ada Boost Classifier	63.24	63.19
4	Extreme Gradient Boosting	76.61	76.12
5	Random Forest Classifier	76.54	76.1
6	Light Gradient Boosting Machine	75.1	75.15
7	Ensemble of above models	77.53	77.65
Age Classification
1	Extra Trees Classifier	70.61	70.55
2	Light Gradient Boosting Machine	72.28	71.39
3	Random Forest Classifier	71.23	69.25
4	CatBoost Classifier	71.96	69.38
5	Extreme Gradient Boosting	73.26	71.02
6	Ensemble of above models	73.87	71.71