0000000000114045

AUTHOR

Mohamed Kas

showing 3 related works from this author

Comprehensive Experimental Analysis of Handcrafted Descriptors for Face Recognition

2018

Over the past few decades, LBP descriptor, which shown its high robustness in extracting discriminative features from an image, has been successfully applied in diverse challenging computer vision applications including face recognition. The efficiency and usability of the LBP operator and its success in various real world applications has inspired the development of much new powerful LBP variants. Indeed, after the appearance of the LBP operator, several renowned extensions and modifications of LBP have been proposed in the literature to the point that it can be difficult to recognize their respective LBP-related strategies, strengths and weaknesses according to a given application, and th…

Computer sciencebusiness.industryFeature extractionComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION020206 networking & telecommunicationsUsability02 engineering and technologyMachine learningcomputer.software_genreFacial recognition systemDiscriminative modelRobustness (computer science)0202 electrical engineering electronic engineering information engineeringTask analysis020201 artificial intelligence & image processingArtificial intelligencebusinesscomputerFERETStrengths and weaknesses2018 International Symposium on Advanced Electrical and Communication Technologies (ISAECT)
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Local Directional Multi Radius Binary Pattern

2018

Face recognition becomes an important task performed routinely in our daily lives. This application is encouraged by the wide availability of powerful and low-cost desktop and embedded computing systems, while the need comes from the integration in too much real world systems including biometric authentication, surveillance, human-computer interaction, and multimedia management. This article proposes a new variant of LBP descriptor referred as Local Directional Multi Radius Binary Pattern (LDMRBP) as a robust and effective face descriptor. The proposed LDMRBP operator is built using new neighborhood topology and new pattern encoding scheme. The adopted face recognition system consists of th…

BiometricsContextual image classificationbusiness.industryComputer scienceFeature vectorFeature extractionComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION020206 networking & telecommunicationsPattern recognition02 engineering and technologyBinary patternFacial recognition systemComputingMethodologies_PATTERNRECOGNITIONHistogram0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingArtificial intelligencebusinessFace detection
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Development of handcrafted and deep based methods for face and facial expression recognition

2021

The research objectives of this thesis concern the development of new concepts for image segmentation and region classification for image analysis. This involves implementing new descriptors, whether color, texture, or shape, to characterize regions and propose new deep learning architectures for the various applications linked to facial analysis. We restrict our focus on face recognition and person-independent facial expressions classification tasks, which are more challenging, especially in unconstrained environments. Our thesis lead to the proposal of many contributions related to facial analysis based on handcrafted and deep architecture.We contributed to face recognition by an effectiv…

Apprentissage profondAnalyse d'images faciales[SPI.OTHER] Engineering Sciences [physics]/OtherMachine learningDeep neural networksDeep learningFacial image analysisRéseaux de neurones profondsApprentissage machineClassificationCnn
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