Sebti Foufou, PhD

Sebti Foufou, PhD

Université de Bourgogne

H-index: 29

Europe-France

About Sebti Foufou, PhD

Sebti Foufou, PhD, With an exceptional h-index of 29 and a recent h-index of 21 (since 2020), a distinguished researcher at Université de Bourgogne, specializes in the field of Geometric modeling. Image processing. Product lifecycle management, Data modeles..

His recent articles reflect a diverse array of research interests and contributions to the field:

An automated approach for segmenting numerical control data with controller data for machine tools

QPert: Query Perturbation to improve shape retrieval algorithms

A machine learning framework for enhancing digital experiences in cultural heritage

An integrated framework for the interaction and 3D visualization of cultural heritage

Machine Learning Based Wireless Interference Estimation in a Robotic Force-Seeking Application

3D Quantum Cuts for automatic segmentation of porous media in tomography images

A Methodology for Digital Twins of Product Lifecycle Supported by Digital Thread

CMVP Security Policy Requirements: CMVP Validation Authority Updates to ISO/IEC 24759 and ISO/IEC 19790 Annex B

Sebti Foufou, PhD Information

University

Université de Bourgogne

Position

Prof. of Computer Science France

Citations(all)

5235

Citations(since 2020)

2381

Cited By

4026

hIndex(all)

29

hIndex(since 2020)

21

i10Index(all)

85

i10Index(since 2020)

45

Email

University Profile Page

Université de Bourgogne

Sebti Foufou, PhD Skills & Research Interests

Geometric modeling. Image processing. Product lifecycle management

Data modeles.

Top articles of Sebti Foufou, PhD

An automated approach for segmenting numerical control data with controller data for machine tools

Authors

William Z Bernstein,Vincenzo J Ferrero,Sebti Foufou

Journal

Journal of Computing and Information Science in Engineering

Published Date

2024/4

Developing a more automated industrial digital thread is vital to realize the smart manufacturing and industry 4.0 vision. The digital thread allows for efficient sharing across product lifecycle stages. Current techniques are not robust in relating downstream data, such as manufacturing and inspection information, back to design for better decision making. We previously presented a methodology that aligns numerical control (NC) code, a standard for representing machine tool instructions, to controller data represented in MTConnect, a standard that provides a vocabulary for generalizing execution logs from different machine tools and devices. This paper extends our previous work by automating the tool identification using a k-means clustering algorithm to refine the alignment of the data. In doing so, we compare different distance techniques to analyze the spatial-temporal registration of the two datasets, ie, the NC …

QPert: Query Perturbation to improve shape retrieval algorithms

Authors

Abdelhakim Benkrama,Bilal Mokhtari,Kamal Eddine Melkemi,Sebti Foufou,Omar Boudraa,Dominique Michelucci

Journal

Multimedia Tools and Applications

Published Date

2024/3

Although there is a wide range of shape descriptors available in the literature, most of them are restricted to a specific class of shapes and no one can achieve satisfactory shape retrieval results when used with different classes of shapes. Introducing new descriptors, improving, or merging existing descriptors are potential strategies for enhancing shape retrieval algorithms. In this paper, we propose a Query Perturbation-based (QPert) method for shape retrieval. QPert perturbs the query shape to create copies or clones that are closer than the query itself to the database shapes. Clones are created by adding a small noise to the coordinates of a randomly selected subset of mesh vertices or applying genetic operators between existing clones. A Genetic Algorithm (GA) gradually develops a population of clones so that the fittest clones get closer and closer to their most similar shapes in the database. The GA is …

A machine learning framework for enhancing digital experiences in cultural heritage

Authors

Abdelhak Belhi,Abdelaziz Bouras,Abdulaziz Khalid Al-Ali,Sebti Foufou

Journal

Journal of Enterprise Information Management

Published Date

2023/4/24

PurposeDigital tools have been used to document cultural heritage with high-quality imaging and metadata. However, some of the historical assets are totally or partially unlabeled and some are physically damaged, which decreases their attractiveness and induces loss of value. This paper introduces a new framework that aims at tackling the cultural data enrichment challenge using machine learning.Design/methodology/approachThis framework focuses on the automatic annotation and metadata completion through new deep learning classification and annotation methods. It also addresses issues related to physically damaged heritage objects through a new image reconstruction approach based on supervised and unsupervised learning.FindingsThe authors evaluate approaches on a data set of cultural objects collected from various cultural institutions around the world. For annotation and classification part of …

An integrated framework for the interaction and 3D visualization of cultural heritage

Authors

Abdelhak Belhi,Hosameldin Osman Ahmed,Taha Alfaqheri,Abdelaziz Bouras,Abdul H Sadka,Sebti Foufou

Journal

Multimedia Tools and Applications

Published Date

2023/1/11

In this study, the aim is to design and develop a 3D acquisition, visualization, and interaction framework to preserve cultural heritage and provide new ways to enable museum visitors and cultural audiences to virtually interact with cultural objects. Indeed, cultural assets are nowadays at higher risk and most cultural institutions prohibit visitors from physically manipulating their collections. The main motivation behind our framework is to enable end-user interaction with high valuable cultural objects while addressing cost-effectiveness concerns as well as minimizing the time required to digitize and generate 3D models of cultural heritage objects. The design idea of our framework is to allow interaction with the protected assets’ 3D representation using a real-world 3D screen equipped with a depth sensor namely the leap motion controller. Our framework is an end-to-end solution that optimizes all the stages of the 3D …

Machine Learning Based Wireless Interference Estimation in a Robotic Force-Seeking Application

Authors

Richard Candell,Richard Candell,Mohamed Kashef,Karl Montgomery,Yongkang Liu,Sebti Foufou

Published Date

2022/2/16

Wide deployment of wireless communications plays an essential role in the vision of future cyber-physical systems (CPSs), which includes massive transfer of automation information. Many practical considerations of industrial CPSs affect the success of the deployment of industrial wireless networks, and, thus, can inhibit their widespread adoption. These considerations include multi-path propagation, network congestion, and jamming interference. Jamming is of chief concern when wireless is used for mission critical or safety integrated systems. In this paper, an experimental platform consisting of a robot arm depressing a spring mechanism with a wireless force-feedback control algorithm is constructed. The robot applies downward pressure on a spring assembly until a predetermined force is detected and transmitted successfully to the controller under varying levels of sustained interference. Machine learning is used to learn and predict the signal-to-interference level of the communication link solely using position information from an independent vision tracking system. Various supervised learning algorithms are investigated and rated according to their performance.

3D Quantum Cuts for automatic segmentation of porous media in tomography images

Authors

Junaid Malik,Serkan Kiranyaz,Riyadh I Al-Raoush,Olivier Monga,Patricia Garnier,Sebti Foufou,Abdelaziz Bouras,Alexandros Iosifidis,Moncef Gabbouj,Philippe C Baveye

Journal

Computers & Geosciences

Published Date

2022/2/1

Binary segmentation of volumetric images of porous media is a crucial step towards gaining a deeper understanding of the factors governing biogeochemical processes at minute scales. Contemporary work primarily revolves around primitive techniques based on global or local adaptive thresholding that have known common drawbacks in image segmentation. Moreover, the absence of a unified benchmark prohibits quantitative evaluation, which further undermines the impact of existing methodologies. In this study, we tackle the issue on both fronts. First, by drawing parallels with natural image segmentation, we propose a novel, and automatic segmentation technique, 3D Quantum Cuts (QCuts-3D) grounded on a state-of-the-art spectral clustering technique. Secondly, we curate and present a publicly available dataset of 68 multiphase volumetric images of porous media with diverse solid geometries, along with …

A Methodology for Digital Twins of Product Lifecycle Supported by Digital Thread

Authors

Laetitia V Monnier,Guodong Shao,Sebti Foufou

Published Date

2022/10/30

Technological advancements have led to the transition of manufacturing industries to Smart Manufacturing and Industry 4.0. Promising concepts such as Digital Twin and Digital Thread could help speed up the transition. One benefit of using digital twins is to enable continuity of lifecycle information. However, currently, most digital-twin implementations focus on modeling a particular lifecycle stage of a physical element in “silos”. This makes companies missing out on up to 65% of possible value of digital twin investments. This also results in it challenging to incorporate diverse data streams from different lifecycle stages. Digital thread has been used to represent information flow along the product lifecycle. Using information across product lifecycle stages will facilitate interoperability and reusability of digital twins. Because data from each lifecycle stage could be accessed and managed systematically, this will …

CMVP Security Policy Requirements: CMVP Validation Authority Updates to ISO/IEC 24759 and ISO/IEC 19790 Annex B

Authors

David Hawes,Alexander Calis,Roy Crombie

Published Date

2022/10/17

NIST Special Publication (SP) 800-140Br1 is to be used in conjunction with ISO/IEC 19790 Annex B and ISO/IEC 24759 section 6.14. The special publication modifies only those requirements identified in this document. SP 800-140Br1 also specifies the content of the information required in ISO/IEC 19790 Annex B. As a validation authority, the Cryptographic Module Validation Program (CMVP) may modify, add, or delete Vendor Evidence (VE) and/or Test Evidence (TE) specified under paragraph 6.14 of the ISO/IEC 24759 and specify the order of the security policy as specified in ISO/IEC 19790: 2012 B. 1.

Predicting car sale time with data analytics and machine learning

Authors

Hamid Ahaggach,Lylia Abrouk,Sebti Foufou,Eric Lebon

Published Date

2022/7/10

There is no doubt that marketing is an important step in Product Lifecycle Management (PLM) and obviously decreasing time-to-market is crucial to reduce storage costs and increase profit. This paper aims to improve marketing strategies in the automotive field for car dealers and car selling supply chain. Due to the cost of new cars and the high risk of car value depreciation it becomes necessary for car dealers to know which type of cars can be sold faster than others, this will allow dealers to adapt their marketing strategies and satisfy the need of their customers. We propose to use data analysis and machine learning algorithms to address this problem and create models to help these companies in their decision-making processes. In our experiments, we used sale data from two big dealers of multi-maker cars. The dataset contains the sale history of around 73200 cars over a period of 8 years. We compared the …

Study and evaluation of pre-trained CNN networks for cultural heritage image classification

Authors

Abdelhak Belhi,Hosameldin Osman Ahmed,Taha Alfaqheri,Abdelaziz Bouras,Abdul Hamid Sadka,Sebti Foufou

Journal

Data Analytics for Cultural Heritage: Current Trends and Concepts

Published Date

2021

The classification of digital images is an essential task during the restoration and preservation of cultural heritage (CH). In computer vision, cultural heritage classification relies on the classification of asset images regarding a certain task such as type, artist, genre, style identification, etc. CH classification is challenging as various CH asset images have similar colors, textures, and shapes. In this chapter, the aim is to study and evaluate the use of pre-trained deep convolutional neural networks such as VGG16, VGG-19, ResNet50, and Inception-V3 for cultural heritage images classification using transfer learning techniques. The main idea is to start with CNN models previously trained for definite tasks with specific datasets and classes, instead of designing a full stand-alone CNN-based model. Two image datasets are used to validate the performance of these models in CH images classification. The …

A cost-effective 3d acquisition and visualization framework for cultural heritage

Authors

Hosameldin Osman Ahmed,Abdelhak Belhi,Taha Alfaqheri,Abdelaziz Bouras,Abdul H Sadka,Sebti Foufou

Published Date

2021

Museums and cultural institutions, in general, are in a constant challenge of adding more value to their collections. The attractiveness of assets is practically tightly related to their value obeying the offer and demand law. New digital visualization technologies are found to give more excitements, especially to the younger generation as it is proven by multiple studies. Nowadays, museums around the world are currently trying to promote their collections through new multimedia and digital technologies such as 3D modeling, virtual reality (VR), augmented reality (AR), and serious games. However, the difficulty and the resources required to implement such technologies present a real challenge. Through this paper, we propose a 3D acquisition and visualization framework aiming mostly at increasing the value of cultural collections. This framework preserves cost-effectiveness and time constraints while still introducing …

Robust design of an evolutionary algorithm for machining optimization problems

Authors

Jean-Louis Vigouroux,Laurent Deshayes,Sebti Foufou,James J Filliben,Lawrence A Welsch,Alkan Donmez

Published Date

2021/10/12

In this paper, a methodology for the robust design of an evolutionary algorithm is presented. The evolutionary algorithm (EA) is studied with the intention to solve machining optimization problems having highly non linear constraints and uncertainties. A turning optimization problem, solved previously with classic optimization algorithms, serves as a basis for the investigation of the EA. The parameters of the problem now can be modified in a certain range, and statistical engineering methods are used to find a unique set of algorithm parameters giving robust results.

Classifying Data Mapping Techniques to Facilitate the Digital Thread and Smart Manufacturing

Authors

Laetitia V Monnier,William Z Bernstein,Sebti Foufou

Published Date

2021/7/11

Representing manufacturing information and maintaining data interoperability are crucial to achieving Smart Manufacturing (SM), also referred to as Industry 4.0. Throughout the Product Lifecycle (PL), data standards have been developed in “silos” based on the specific needs of each PL stage. Dealing with multiple data standards, formats, and representations makes it challenging to transfer information throughout PL stages. Mapping techniques and data translation methods can aid in solving such data heterogeneity challenges. Recent works have demonstrated that general techniques for data mapping and analytics can facilitate more holistic viewpoints. Such viewpoints can help stakeholders make better decisions at the design phase, wherein cost and PL impacts such as those associated with environmental sustainability, are mostly fixed. This paper focuses on analyzing the potential of different types of …

The NIST IrisDaily Dataset: Description and Initial Analysis

Authors

JAmes Matey

Published Date

2021/5/4

This paper describes a dataset, IrisDaily-NIST, that is under construction by NIST. The purpose of the dataset is to enable evaluation of long and short term variability in comparison scores under optimal conditions. At the present, this dataset has (nearly) daily iris images of a single subject collected with a commercial iris camera over a period of approximately 4 months.

Smart Manufacturing Testbed for the Advancement of Wireless Adoption in the Factory

Authors

Richard Candell,Yongkang Liu,Mohamed Kashef,Karl Montgomery,Sebti Foufou

Published Date

2020/7/5

Wireless communication is a key enabling technology central to the advancement of the goals of the Industry 4.0 smart manufacturing concept. Researchers at the National Institute of Standards and Technology are constructing a testbed to aid in the adoption of wireless technology within the factory workcell and other harsh industrial radio environments. In this paper the authors present a new industrial wireless testbed design that motivates academic research and is relevant to the needs of industry. The testbed is designed to serve as both a demonstration and research platform for the wireless workcell. The work leverages lessons learned from past testbed incarnations that included a dual robot machine tending scenario and a force-torque seeking robot arm apparatus. This version of the testbed includes computational and communication elements such that the operation of the physical system is …

A graph database approach to wireless iiot workcell performance evaluation

Authors

Richard Candell,Mohamed Kashef,Yongkang Liu,Karl Montgomery,Sebti Foufou

Published Date

2020/2/26

The workcell is considered a main building block of various industrial settings. Hence, it is examined as a primary testing environment for studying wireless communication techniques in factory automation processes. A new testbed was recently designed and developed to facilitate such studies in workcells by replicating various data flows in an emulated production environment. In this paper, an approach to storing and analyzing network performance data from a manufacturing factory workcell is introduced. A robotic testbed was constructed using two collaborative grade robot arms, machine emulators, and wireless communication devices. A graph database approach was implemented to capture network and operational event data among the components within the testbed. A schema is proposed, developed, and elaborated; a database is then populated with events from the testbed, and the resulting graph is …

Optimizing query perturbations to enhance shape retrieval

Authors

Bilal Mokhtari,Kamal Eddine Melkemi,Dominique Michelucci,Sebti Foufou

Published Date

2020

3D Shape retrieval algorithms use shape descriptors to identify shapes in a database that are the most similar to a given key shape, called the query. Many shape descriptors are known but none is perfect. Therefore, the common approach in building 3D Shape retrieval tools is to combine several descriptors with some fusion rule. This article proposes an orthogonal approach. The query is improved with a Genetic Algorithm. The latter makes evolve a population of perturbed copies of the query, called clones. The best clone is the closest to its closest shapes in the database, for a given shape descriptor. Experimental results show that improving the query also improves the precision and completeness of shape retrieval output. This article shows evidence for several shape descriptors. Moreover, the method is simple and massively parallel.

Interference level estimation using machine learning in a robotic force-seeking scenario

Authors

Richard Candell,Mohamed T Hany,Karl R Montgomery,Yongkang Liu,Sebti Foufou

Published Date

2020/12/31

Wireless communications plays an essential role in the future cyber-physical systems vision which includes having more sensors and actuators, and, hence, more information transferred through wireless. In this article, we consider an industrial use case of a robot arm control system equipped with a force-torque sensor. Movement of the arm is tracked by a vision-based ground truth measurement system. Movement of the arm is controlled by a robot controller applying a downward pressure on a spring assembly until a predetermined force is detected. The remote vision-based observer provides readings about the position of the robot arm where these readings are used to estimate the signal-to-interference ratio of the wireless link. A supervised machine learning approach is used for the wireless channel quality estimation. In this paper, we study the impact of various system features on the performance of various …

Machine learning and digital heritage: the CEPROQHA project perspective

Authors

Abdelhak Belhi,Houssem Gasmi,Abdelaziz Bouras,Taha Alfaqheri,Akuha Solomon Aondoakaa,Abdul H Sadka,Sebti Foufou

Published Date

2020

Through this paper, we aim at investigating the impact of artificial intelligence technologies on cultural heritage promotion and long-term preservation in terms of digitization effectiveness, attractiveness of the assets, and value empowering. Digital tools have been validated to yield sustainable and yet effective preservation for multiple types of content. For cultural data, however, there are multiple challenges in order to achieve sustainable preservation using these digital tools due to the specificities and the high-quality requirements imposed by cultural institutions. With the rise of machine learning and data science technologies, many researchers and heritage organizations are nowadays searching for techniques and methods to value and increase the reliability of cultural heritage digitization through machine learning. The present study investigates some of these initiatives highlighting their added value and …

Investigating low-delay deep learning-based cultural image reconstruction

Authors

Abdelhak Belhi,Abdulaziz Khalid Al-Ali,Abdelaziz Bouras,Sebti Foufou,Xi Yu,Haiqing Zhang

Journal

Journal of Real-Time Image Processing

Published Date

2020/12

Numerous cultural assets host a great historical and moral value, but due to their degradation, this value is heavily affected as their attractiveness is lost. One of the solutions that most heritage organizations and museums currently choose is to leverage the knowledge of art and history experts in addition to curators to recover and restore the damaged assets. This process is labor-intensive, expensive and more often results in just an assumption over the damaged or missing region. In this work, we tackle the issue of completing missing regions in artwork through advanced deep learning and image reconstruction (inpainting) techniques. Following our analysis of different image completion and reconstruction approaches, we noticed that these methods suffer from various limitations such as lengthy processing times and hard generalization when trained with multiple visual contexts. Most of the existing learning …

See List of Professors in Sebti Foufou, PhD University(Université de Bourgogne)

Sebti Foufou, PhD FAQs

What is Sebti Foufou, PhD's h-index at Université de Bourgogne?

The h-index of Sebti Foufou, PhD has been 21 since 2020 and 29 in total.

What are Sebti Foufou, PhD's top articles?

The articles with the titles of

An automated approach for segmenting numerical control data with controller data for machine tools

QPert: Query Perturbation to improve shape retrieval algorithms

A machine learning framework for enhancing digital experiences in cultural heritage

An integrated framework for the interaction and 3D visualization of cultural heritage

Machine Learning Based Wireless Interference Estimation in a Robotic Force-Seeking Application

3D Quantum Cuts for automatic segmentation of porous media in tomography images

A Methodology for Digital Twins of Product Lifecycle Supported by Digital Thread

CMVP Security Policy Requirements: CMVP Validation Authority Updates to ISO/IEC 24759 and ISO/IEC 19790 Annex B

...

are the top articles of Sebti Foufou, PhD at Université de Bourgogne.

What are Sebti Foufou, PhD's research interests?

The research interests of Sebti Foufou, PhD are: Geometric modeling. Image processing. Product lifecycle management, Data modeles.

What is Sebti Foufou, PhD's total number of citations?

Sebti Foufou, PhD has 5,235 citations in total.

What are the co-authors of Sebti Foufou, PhD?

The co-authors of Sebti Foufou, PhD are Professor Zahir Tari, Eswaran Subrahmanian, Abdelaziz Bouras, Ridha Hamila, Ahmed Ben Saïd, Yohan Fougerolle.

    Co-Authors

    H-index: 46
    Professor Zahir Tari

    Professor Zahir Tari

    RMIT University

    H-index: 38
    Eswaran Subrahmanian

    Eswaran Subrahmanian

    Carnegie Mellon University

    H-index: 30
    Abdelaziz Bouras

    Abdelaziz Bouras

    Qatar University

    H-index: 29
    Ridha Hamila

    Ridha Hamila

    Qatar University

    H-index: 13
    Ahmed Ben Saïd

    Ahmed Ben Saïd

    Qatar University

    H-index: 13
    Yohan Fougerolle

    Yohan Fougerolle

    Université de Bourgogne

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