An Intelligent Personal Assistant Relevance | ||
| The International Undergraduate Research Conference | ||
| Volume 5, Issue 5, 2021, Pages 469-475 PDF (512.2 K) | ||
| Document Type: Original Article | ||
| DOI: 10.21608/iugrc.2021.246532 | ||
| Authors | ||
| Beshoy Nady Adly1; Tomas Azer Ewnan1; Menna Mohammed Hagrss1; EL shimaa Mohammed Slime1; Marian Nady1; Mahmoud Hesham1; Norhan Mohammed1; Shihab Raafat1; Emad S. Othman2 | ||
| 1Senior Member IEEE - Region 8, High Institute for Computers and Information Systems, AL-Shorouk Academy, Cairo – Egypt. | ||
| 2Senior Member IEEE - Region 8, High Institute for Computers and Information Systems, AL-Shorouk Academy, Cairo – Egypt. | ||
| Abstract | ||
| Despite the great development that has occurred in deep learning field, the problem still persists, and this negates the main reason for creating software, which is to facilitate business, trade, transactions, communication, and others. Deep learning methods are computational models that are composed of multiple processing layers to learn representations of data with multiple levels of abstraction. In this paper, we implemented internet searching on Google and YouTube using voice commands then displaying results, recognizing faces and fingerprints for users to improve security, gathering information, answering questions and reading them to the user, fully controlling all files and folders on the computer and carrying out all common operations on them such as (add, delete, move, rename, create).The system uses Speech Recognition API introduced by Google, Local Binary Patterns Histogram (LBPH) to perform face/object recognition. The evaluation is performed using Histogram analysis and the results show superiority of the model and the efficiency of LBHP algorithm in various applications for facial recognition. | ||
| Keywords | ||
| Deep Learning; Face Recognition; Object Recognition; Local Binary Patterns Histogram (LBPH) | ||
|
Statistics Article View: 72 PDF Download: 78 |
||
