This project is the subject of my internship as a machine learning engineer at the Southeast Digital Economic Development Institute (Quzhou). It aims to learn the human’s aerobic capacity from the exercise data (e.g., heart rate and speed) of undergraduate students, and thus a customized exercise program can be provided for each student. This project is co-funded by the National Student Innovation Training Program and Zhejiang Province New Talent Program.
Compared with a flat fingerprint, the rolled fingerprint has a larger fingerprint area and can be extracted more minutiae. It has high requirements in many fields, not only in the military environment or the police field but also in many civil application fields. The challenge that has been troubled for a long time is that contact-based rolled fingerprint registration is easy to cause obvious distortion without human experts’ supervision, which has a negative impact on fingerprint recognition performance. Due to the elastic deformation of fingertips, the mosaicking gaps in the rolled fingerprint are usually visible but challenging to locate. To address these problems, we propose a novel rolled fingerprint construction algorithm called BlockRFC (Block-based Rolled Fingerprint Construction). Please see our papers for more details.