Accueil › Annuaire des chercheurs › Slim Ben Saoud
Slim Ben Saoud
Affiliation : University of Carthage
- 44Publications (affiliation tunisienne)
- 65Publications au total
- 473Citations
- 11Indice h
Profil de recherche
Slim Ben Saoud compte 44 publications référencées (2002–2023). Ses travaux paraissent principalement dans « International Conference on Design & Technology of Integrated Systems in Nanoscale Era (DTIS) », « IEEE International Conference on Advanced Systems and Emergent Technologies (IC_ASET) » et « World Symposium on Computer Applications & Research (WSCAR) ». Son article le plus cité, « Hybrid CNN-SVM classifier for efficient depression detection system » (2020), a été cité 73 fois. 7 de ces publications datent des trois dernières années d’activité. Ses travaux sont cosignés avec au moins 12 chercheurs.
C’est vous ? Faites connaître vos travaux
Créez gratuitement votre profil DzCademia et ajoutez vos articles : ils apparaîtront plus facilement sur Google et dans les assistants d’IA comme ChatGPT. Plus de personnes pourront vous lire et vous citer.
Créer mon profil gratuit Ajouter mes publicationsDomaines de recherche
- Embedded Systems Design Techniques
- Embedded Systems and FPGA Design
- Embedded Systems and FPGA Applications
- Real-Time Systems Scheduling
- Real-time simulation and control systems
Publications (44)
- CNN inference acceleration on limited resources FPGA platforms_epilepsy detection case study
- Acceleration of convolutional neural network based diabetic retinopathy diagnosis system on field programmable gate array
- FPGA-based implementation of classification techniques: A survey
- Accelerating Deep Neural Networks implementation: A survey
- A novel epileptic seizure detection system using scalp EEG signals based on hybrid CNN-SVM classifier
- Optimization of CNN model for image classification
- Hybrid BYOL-ViT: Efficient approach to deal with small datasets
- Hybrid CNN-SVM classifier for efficient depression detection system
- CNN for object recognition implementation on FPGA using PYNQ framework
- Speech Emotion Recognition: Models Implementation & Evaluation
- FPGA implementation of EEG signal analysis system for the detection of epileptic seizure
- FW_IP: A flexible and lightweight hardware firewall for NoC-based systems
- FPGA implementation of self-reconfigurable fuzzy logic controller
- Problems and challenges of emerging technology networks−on−chip: A review
- Reconfigurable SoC FPGA based: Overview and trends
- AFDX simulation based on TTEthernet model under OMNeT++
- Toward on hardware firewalling of networks-on-chip based systems
- An Efficient Technique for Hardware/Software Partitioning Process in Codesign
- The design of a Network-On-Chip architecture based on an avionic protocol
- Impact of Hardware/Software Partitioning and MicroBlaze FPGA Configurations on the Embedded Systems Performances
- Design methodologies impact on the embedded system performances: Case of cryptographic algorithm
- Modeling of a heterogeneous AFDX-CAN network gateway
- Investigating the use of the AFDX protocol as a Network-On-Chip
- Exploring SoPC technology and RTOS issues for industrial motor control
- Impact of the Linux Real-time Enhancements on the System Performances for Multi-core Intel Architectures
- Performance Analysis of FPGA Architectures based Embedded Control Applications
- Runtime Reconfigurable MPSoC architecture for control drive system
- Model-based design approach for embedded digital controllers design
- Flexible Implementation of Industrial Real-Time Servo Drive System
- Real-time reconfigurable SoC for process control
- Hw acceleration for FPGA-based drive controllers
- High Level Synthesis of Real Time embedded emulating system for Motor controller
- Modelling of sigma-delta converters in SystemC for the electromechanical systems control
- Designing and building embedded environment for robotic control application
- Servo drive system based on programmable SoC architecture
- Hard and soft-core implementation of embedded control application using RTOS
- MPSoC design of RT control applications based on FPGA SoftCore processors
- RTOS for SoC embedded control applications
- FPGA HardCore single processor implementation of RT control applications
- Hardware design and implementation of digital controller for parallel active filters
- Implementation of a fuzzy logic tracking path algorithm on a field programmable gate array
- An FPGA hardware implementation of the Rijndael block cipher
- Design and implementation of a neural command rule on a FPGA circuit
- Parallel architectures applied real time emulation [of power apparatus]
Revues de publication
- International Conference on Design & Technology of Integrated Systems in Nanoscale Era (DTIS) × 9
- IEEE International Conference on Advanced Systems and Emergent Technologies (IC_ASET) × 8
- World Symposium on Computer Applications & Research (WSCAR) × 3
- IEEE International Symposium on Industrial Electronics (ISIE) × 3
- Annual Conference of the IEEE Industrial Electronics Society (IECON) × 3
- International Journal of Informatics and Communication Technology (IJ-ICT) × 2
Publications par année
- 20232
- 20215
- 20202
- 20191
- 20183
- 20174
- 20161
- 20144
- 20122
- 20116
Collaborations
Établissements partenaires : National Institute of Applied Science and Technology · Tunisia Polytechnic School · Université Tunis Carthage · Faculté de médecine de Tunis · Tunis El Manar University
Co-auteurs
- Slim Ben Othman
- Ahmed Karim Ben Salem
- Afef Saidi
- Hedi Abdelkrim
- Ahmed Ben Achballah
- Meriam Dhouibi
- Imène Mhadhbi
- Nejla Rejeb
- Nabil Litayem
- Meftah Ghrissi
- H. Abdelkrim
- Riadh Saidia
Données bibliographiques issues d’OpenAlex (base ouverte).
Pourquoi choisir Dzcademia ?
Pour donner à vos travaux plus de chances d’être découverts et recommandés par les IA. Profils, articles et communications : donnez à votre recherche une présence publique structurée. Les métadonnées intégrées aident les moteurs de recherche et les assistants IA à identifier vos travaux et à comprendre leurs références.
Commenter avec Google
Connecte-toi avec Google pour commenter directement sur cette page.