World Journal of Engineering Research and Technology (WJERT) has indexed with various reputed international bodies like : Google Scholar , Index Copernicus , Indian Science Publications , SOCOLAR, China , International Institute of Organized Research (I2OR) , Cosmos Impact Factor , Research Bible, Fuchu, Tokyo. JAPAN , Scientific Indexing Services (SIS) , Jour Informatics (Under Process) , UDLedge Science Citation Index , International Impact Factor Services , International Scientific Indexing, UAE , International Society for Research Activity (ISRA) Journal Impact Factor (JIF) , International Innovative Journal Impact Factor (IIJIF) , Science Library Index, Dubai, United Arab Emirates , Scientific Journal Impact Factor (SJIF) , Science Library Index, Dubai, United Arab Emirates , Eurasian Scientific Journal Index (ESJI) , Global Impact Factor (0.342) , IFSIJ Measure of Journal Quality , Web of Science Group (Under Process) , Directory of Research Journals Indexing , Scholar Article Journal Index (SAJI) , International Scientific Indexing ( ISI ) , Scope Database , 

World Journal of Engineering
Research and Technology

( An ISO 9001:2015 Certified International Journal )

An International Peer Reviewed Journal for Engineering Research and Technology

ISSN 2454-695X

Impact Factor : 5.924

ICV : 79.45

News & Updation

  • Article Invited for Publication

    Article are invited for publication in WJERT Coming Issue

  • ICV

    WJERT Rank with Index Copernicus Value 79.45 due to high reputation at International Level

  • WJERT New Impact Factor

    Its our Pleasure to Inform you that WJERT Impact Factor has been increased from  5.549 to 5.924 due to high quality Publication at International Level


    SEPTEMBER 2022 Issue has been successfully launched on 1 September 2022.

  • New Issue Published

    Its Our pleasure to inform you that, WJERT 1 September 2022 Issue has been Published, Kindly check it on




*Bharath J. and Dr. R. Balakrishna


In today's age of networked multimedia information access, face recognition has triggered a lot of curiosity. Although great progress has been made in the field of face detection and recognition for security, identity, and attendance purposes, there are still obstacles in the way of reaching human-level accuracy. Faces have the unique ability to aid human recognition, which is important in surveillance applications. Furthermore, the non-intrusive nature of these technologies leads to high collectability and acceptance, making them ideally suited for wider use. Machine learning algorithms play a critical role in facial recognition. Even if face methods focus more on face descriptor and feature extraction methods, classification techniques have an impact on recognition performance. There are various traditional classification techniques. Face detection in noisy scenes is the starting point for face recognition, which is followed by pre-processing, normalising the face samples data, feature extraction, and classification. Our experiments show that our face identification system is reliable, trustworthy, and durable, and that it can be employed in a real-world situation.

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