@article { author = {H. Alaoui, Hachem and Hachem, Elkaber and Ziti, Cherif and Karim, Mohammed}, title = {The Use of Local Sensitive Hashing for E-learner Face Identification}, journal = {The ISC International Journal of Information Security}, volume = {12}, number = {3}, pages = {1-5}, year = {2020}, publisher = {Iranian Society of Cryptology}, issn = {2008-2045}, eissn = {2008-3076}, doi = {10.22042/isecure.2021.271051.612}, abstract = {Because face can reveal so much hidden information, we need to interpret these data and benefit from them. Hence, our paper shows a new and productive facial image representation based on local sensitive hashing (LSH). This strategy makes it conceivable to recognize the students who pursue their preparation in our learning training; during every session, an image of the learner will be taken by the webcam to be compared to that already stored in the database. As soon as the learner is recognized, he/she must be arranged in the accordion to an appropriate profile that takes into consideration his/her weaknesses and strength, which is conducted with the help of the J48 as a predictive study. Furthermore, we utilize a light processing module on the client device with a compact code in order that we can have a lot of in formation transmission capable to send the component over the network and to have the option to record many photos in an enormous database in the cloud.}, keywords = {cloud,Facial Image,J48,Learning Platform,LSH,PROFILE}, url = {https://www.isecure-journal.com/article_128625.html}, eprint = {https://www.isecure-journal.com/article_128625_40e4977dbdd80892bd23380e895e0e1f.pdf} }