14 May 2026
Neural Network Quantization for FPGA: A Unified Taxonomy and Survey of Methods, Platforms, and DeploymentPublisher siteActive, last published 2026
In advanced neural network applications
Noura
Jariri
Scholar“Research focused on Advanced Neural Network Applications and adjacent fields.”
Ibn Tofail University
Morocco
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22
Citations
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01 · About the work
What I study
oura Jariri is a researcher working on Advanced Neural Network Applications. A fuller summary will appear once they update their profile.
02 · Reach
Publication output and reach
Noura's work has been cited 22 times across 3 active years. Bars show publications per year; the line shows cumulative citation totals across publications first appearing in each year.
03 · Research focus
Topics
Advanced Neural Network Applications×5Vehicle License Plate Recognition×2
04 · Where I am
Affiliations
Affiliation on published researchUniversité Ibn-Tofail, MoroccoDrawn from the institution listed on this researcher’s published work.
05 · Selected work
Recent publications
8 works4 Apr 2026Open access
A Hardware-Aware Analysis of PTQ and QAT Quantized CNNs for Object Detection on FPGAPublisher siteEngineering Technology & Applied Science Research, Advanced Neural Network Applications
22 Oct 2025
Detection and Instance Segmentation of Road Markings and Lane Lines Using YOLOv11-SEG for ADAS and Autonomous DrivingPublisher site6 Oct 2025Open access4cites
A Real-Time Vehicle Detection System for ADAS in Autonomous Vehicles Using YOLOv11 Deep Neural Network on Embedded Edge PlatformsPublisher siteEngineering Technology & Applied Science Research, Advanced Neural Network Applications
19 Jun 20252cites
Real-Time Vehicle Detection and Instance Segmentation for ADAS Using the YOLOv11-SEG Model: A Deep Learning ApproachPublisher site15 May 20256cites
Enhanced Deep Neural Network-Based Vehicle Detection System Using YOLOv11 for Autonomous VehiclesPublisher site19 Feb 20251cites
Evaluating HLS4ML For Converting a CNN Model Into High Level SynthesisPublisher site31 May 2024Open access9cites
Adaptive K values and training subsets selection for optimal K-NN performance on FPGAPublisher siteJournal of King Saud University - Computer and Information Sciences, Anomaly Detection Techniques and Applications
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