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Hardware/Software Co-Design of a Traffic Sign Recognition System Using Zynq FPGAs

https://doi.org/10.3390/electronics4041062
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Inferred edges come from two machine sources: sweeps of open repository metadata (mostly SSRN and Zenodo), and a bulk OpenAlex citation snapshot. Every row below is labelled with the one it came from. Neither is a complete citation index — absence here is not evidence of absence.

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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1002/9780470828519openalex-snapshot
Design for Embedded Image Processing on FPGAs
inferredcites →https://doi.org/10.1007/978-3-662-04186-4openalex-snapshot
Color Image Processing and Applications
inferredcites →https://doi.org/10.1016/0146-664x(80)90047-7openalex-snapshot
Color information for region segmentation
inferredcites →https://doi.org/10.1016/j.cviu.2007.09.014openalex-snapshot
Speeded-Up Robust Features (SURF)
inferredcites →https://doi.org/10.1109/asscc.2011.6123600openalex-snapshot
A 92mW real-time traffic sign recognition system with robust light and dark adaptation
inferredcites →https://doi.org/10.1109/civts.2014.7009470openalex-snapshot
A GPU-based real-time traffic sign detection and recognition system
inferredcites →https://doi.org/10.1109/cvrs.2012.6421274openalex-snapshot
Salient traffic sign recognition based on sparse representation of visual perception
inferredcites →https://doi.org/10.1109/date.2010.5457147openalex-snapshot
Design of an automotive traffic sign recognition system targeting a multi-core SoC implementation
inferredcites →https://doi.org/10.1109/eit.2014.6871793openalex-snapshot
Real-time traffic sign recognition based on Zynq FPGA and ARM SoCs
inferredcites →https://doi.org/10.1109/hpec.2013.6670350openalex-snapshot
Real-time traffic sign detection using SURF features on FPGA
inferredcites →https://doi.org/10.1109/iccv.1999.790410openalex-snapshot
Object recognition from local scale-invariant features
inferredcites →https://doi.org/10.1109/icit.2013.6505826openalex-snapshot
Design and implementation of an automatic traffic sign recognition system on TI OMAP-L138
inferredcites →https://doi.org/10.1109/ijcnn.2011.6033589openalex-snapshot
Traffic sign recognition with multi-scale Convolutional Networks
inferredcites →https://doi.org/10.1109/ijcnn.2013.6706810openalex-snapshot
Traffic sign detection by ROI extraction and histogram features-based recognition
inferredcites →https://doi.org/10.1109/ijcnn.2013.6706812openalex-snapshot
A robust, coarse-to-fine traffic sign detection method
inferredcites →https://doi.org/10.1109/iscas.2015.7168792openalex-snapshot
A pipeline architecture for traffic sign classification on an FPGA
inferredcites →https://doi.org/10.1109/ivcnz.2009.5378370openalex-snapshot
General traffic sign recognition by feature matching
inferredcites →https://doi.org/10.1109/recosoc.2015.7238089openalex-snapshot
FPGA based traffic sign detection for automotive camera systems
inferredcites →https://doi.org/10.1109/secon.1990.117829openalex-snapshot
A compact navigation system using image processing and fuzzy control
inferredcites →https://doi.org/10.1109/tit.1967.1053964openalex-snapshot
Nearest neighbor pattern classification
inferredcites →https://doi.org/10.1109/tits.2004.828173openalex-snapshot
Visual Sign Information Extraction and Identification by Deformable Models for Intelligent Vehicles
inferredcites →https://doi.org/10.1109/tits.2010.2054084openalex-snapshot
Goal Evaluation of Segmentation Algorithms for Traffic Sign Recognition
inferredcites →https://doi.org/10.1109/tits.2012.2209421openalex-snapshot
Vision-Based Traffic Sign Detection and Analysis for Intelligent Driver Assistance Systems: Perspectives and Survey
inferredcites →https://doi.org/10.1109/tpami.1986.4767851openalex-snapshot
A Computational Approach to Edge Detection
inferredcites →https://doi.org/10.4236/jtts.2013.31001openalex-snapshot
FPGA-Based Traffic Sign Recognition for Advanced Driver Assistance Systems

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.1007/s11227-023-05151-0openalex-snapshot
FPGA implementation of hardware accelerated RTOS based on real-time event handling
inferred← citeshttps://doi.org/10.1007/s11554-016-0657-0openalex-snapshot
Hardware accelerator IP cores for real time Radar and camera-based ADAS
inferred← citeshttps://doi.org/10.1007/s42979-025-04634-6openalex-snapshot
Traffic Sign Classification Using Real-Time GPU-Embedded Systems
inferred← citeshttps://doi.org/10.1016/j.micpro.2024.105101openalex-snapshot
Recent advances in Machine Learning based Advanced Driver Assistance System applications
inferred← citeshttps://doi.org/10.1049/iet-cvi.2016.0082openalex-snapshot
Real‐time embedded implementation of robust speed‐limit sign recognition using a novel centroid‐to‐contour description method
inferred← citeshttps://doi.org/10.1109/access.2022.3230282openalex-snapshot
A Survey of FPGA-Based Vision Systems for Autonomous Cars
inferred← citeshttps://doi.org/10.1109/cisce50729.2020.00099openalex-snapshot
Invoice Code Recognition System Based on FPGA Acceleration
inferred← citeshttps://doi.org/10.1109/icass.2018.8652024openalex-snapshot
Traffic signs recognition with deep learning
inferred← citeshttps://doi.org/10.1109/icce-asia.2016.7804744openalex-snapshot
Low-complexity hardware architecture of traffic sign recognition with IHSL color space for advanced driver assistance systems
inferred← citeshttps://doi.org/10.1109/icinfa.2018.8812379openalex-snapshot
High-Speed Image Processing and Data Transmission Based on Vivado HLS and AXI4-Stream Interface
inferred← citeshttps://doi.org/10.1109/icsccc51823.2021.9478172openalex-snapshot
Traffic Signs Classification using Convolutional Neural Networks: A review
inferred← citeshttps://doi.org/10.1109/instcon69741.2026.11691707openalex-snapshot
Real Time Traffic Sign Recognition for Autonomous Driving System using CNN over FPGA
inferred← citeshttps://doi.org/10.1109/mwscas.2017.8052891openalex-snapshot
Traffic sign recognition based on the NVIDIA Jetson TX1 embedded system using convolutional neural networks
inferred← citeshttps://doi.org/10.1145/3386164.3386175openalex-snapshot
Hardware Scheduler Implementation based on Replicated Resource Architecture for Reconfigurable Systems
inferred← citeshttps://doi.org/10.2478/cjece-2020-0007openalex-snapshot
A Survey about Intelligent Solutions for Autonomous Vehicles based on FPGA
inferred← citeshttps://doi.org/10.3390/electronics10202511openalex-snapshot
An Accuracy-Improved Fixed-Width Booth Multiplier Enabling Bit-Width Adaptive Truncation Error Compensation
inferred← citeshttps://doi.org/10.3390/electronics12102331openalex-snapshot
An Integrated Off-Line Echo Signal Acquisition System Implemented in SoC-FPGA for High Repetition Rate Lidar
inferred← citeshttps://doi.org/10.3390/electronics6020025openalex-snapshot
FPGA and SoC Devices Applied to New Trends in Image/Video and Signal Processing Fields
inferred← citeshttps://doi.org/10.3390/electronics8020211openalex-snapshot
Hardware RTOS: Custom Scheduler Implementation Based on Multiple Pipeline Registers and MIPS32 Architecture
inferred← citeshttps://doi.org/10.3390/electronics8050584openalex-snapshot
Zi-CAM: A Power and Resource Efficient Binary Content-Addressable Memory on FPGAs
inferred← citeshttps://doi.org/10.3390/vehicles7030099openalex-snapshot
Advancements in Embedded Vision Systems for Automotive: A Comprehensive Study on Detection and Recognition Techniques
inferred← citeshttps://doi.org/10.56726/irjmets35451openalex-snapshot
TRAFFIC SIGN RECOGNITION USING DEEP LEARNING
inferred← citeshttps://doi.org/10.7717/peerj.4159openalex-snapshot
Disentangling diatom species complexes: does morphometry suffice?
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