Search Word(s) in Title, Keywords, Authors, and Abstract: Abdelkader Benyettou

Cross-Validation Probabilistic Neural Network Based Face Identification
Abdelhadi Lotfi and Abdelkader Benyettou
Page: 1075~1086, Vol. 14, No.5, 2018
10.3745/JIPS.04.0085
Keywords: Biometrics, Classification, Cross-Validation, Face Identification, Optimization, Probabilistic Neural Networks
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In this paper a cross-validation algorithm for training probabilistic neural networks (PNNs) is presented in order to be applied to automatic face identification. Actually, standard PNNs perform pretty well for small and medium sized databases but they suffer from serious problems when it comes to using them with large databases like those encountered in biometrics applications. To address this issue, we proposed in this work a new training algorithm for PNNs to reduce the hidden layer’s size and avoid over-fitting at the same time. The proposed training algorithm generates networks with a smaller hidden layer which contains only representative examples in the training data set. Moreover, adding new classes or samples after training does not require retraining, which is one of the main characteristics of this solution. Results presented in this work show a great improvement both in the processing speed and generalization of the proposed classifier. This improvement is mainly caused by reducing significantly the size of the hidden layer.


Dorsal Hand Vein Identification Based on Binary Particle Swarm Optimization
Sarah Hachemi Benziane and Abdelkader Benyettou
Page: 268~283, Vol. 13, No.2, 2017
10.3745/JIPS.03.0066
Keywords: Biometrics, BPSO, GPU, Hand Vein, Identification, OTSU
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The dorsal hand vein biometric system developed has a main objective and specific targets; to get an electronic signature using a secure signature device. In this paper, we present our signature device with its different aims; respectively: The extraction of the dorsal veins from the images that were acquired through an infrared device. For each identification, we need the representation of the veins in the form of shape descriptors, which are invariant to translation, rotation and scaling; this extracted descriptor vector is the input of the matching step. The optimization decision system settings match the choice of threshold that allows accepting/rejecting a person, and selection of the most relevant descriptors, to minimize both FAR and FRR errors. The final decision for identification based descriptors selected by the PSO hybrid binary give a FAR =0% and FRR=0% as results.


A Novel Framework for Defining and Submitting Workflows to Service-Oriented Systems
Hayat Bendoukha, Yahya Slimani and Abdelkader Benyettou
Page: 365~383, Vol. 10, No.3, 2014
10.3745/JIPS.02.0003
Keywords: Service Composition, Service-Oriented Computing, Service-Oriented Workflow, UML2BPEL, Workflow
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Service-oriented computing offers efficient solutions for executing complex applications in an acceptable amount of time. These solutions provide important computing and storage resources, but they are too difficult for individual users to handle. In fact, Service-oriented architectures are usually sophisticated in terms of design, specifications, and deployment. On the other hand, workflow management systems provide frameworks that help users to manage cooperative and interdependent processes in a convivial manner. In this paper, we propose a workflow-based approach to fully take advantage of new service-oriented architectures that take the users’ skills and the internal complexity of their applications into account. To get to this point, we defined a novel framework named JASMIN, which is responsible for managing service-oriented workflows on distributed systems. JASMIN has two main components: unified modeling language (UML) to specify workflow models and business process execution language (BPEL) to generate and compose Web services. In order to cover both workflow and service concepts, we describe in this paper a refinement of UML activity diagrams and present a set of rules for mapping UML activity diagrams into BPEL specifications.