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Description

Machine Learning (ML) is a field enhancing the rapid growth of technology. Though use of digital softwares for cheiloscopic investigations have been attempted with limited success, the use of ML based techniques are scarce and seldom have been employed in forensic odontology. The present study aimed to identify cheiloscopic patterns through machine learning based methods and to correlate the segmented patterns with age and gender of individuals.

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Clinical Trials | Health and Medical Administration | Health and Physical Education | Health Services Research | Medical Education | Medical Sciences | Medicine and Health Sciences | Nursing | Oral Biology and Oral Pathology | Primary Care | Scholarship of Teaching and Learning | Teacher Education and Professional Development

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Cheiloscopic Characteristics detection and Pattern Classification by Machine Learning Technique

Machine Learning (ML) is a field enhancing the rapid growth of technology. Though use of digital softwares for cheiloscopic investigations have been attempted with limited success, the use of ML based techniques are scarce and seldom have been employed in forensic odontology. The present study aimed to identify cheiloscopic patterns through machine learning based methods and to correlate the segmented patterns with age and gender of individuals.