السلام عليكم اخوان ورمضان كريم
مشكلتي تصنيف بصمة الاصبع باستخدام اي خوارزمية بحيث تكون المطابقة 90% والسوال كالاتي
Forensics investigation from ngerprint microbes
Recently it was discovered that DNA samples from human ngerprints are unique to individuals. Therefore,
it is possible to get samples from computer keyboards and identify who is using the computer. This task
provides very strong patterns and the recognition rate is high. However, the harder task is to detect which
hand (left or right) the samples are gathered from. In this project, the task is to identify which hand of
an individual touched the computer keyboard. This project involves assessing classication performance of
clinical data gathered from DNA data on computer keyboards. The task is to perform supervised learning
on the dataset and report the classication performance.
With this project it is expected to have close to 90% correct classication or 0.9 ROC AUC scores. In order
to achieve that you are expected to perform attribute selection (note: cross-validation in attribute selection
is also required), and then go for classication with the selected attributes.
Project Groups are free to use ANY classication algorithm/technology that can be found in the literature.
ANY programming language and platforms including machine learning packages (e.g. WEKA, MATLAB,
etc.) can be used. If a group programs the project, the executable build is requested. If a platform like
WEKA is used, the program parameters are requested.