On the public citation graph

Deep Learning and Autonomous Vehicles: Strategic Themes, Applications, and Research Agenda Using SciMAT and Content-Centric Analysis, a Systematic Review

https://doi.org/10.3390/make5030041
0 signed · 109 inferred · view as graph

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.

Is this your work? Sign in with ORCID and put your name on the claims that are yours.
Claim with ORCID
Reference health. See whether every reference in this work resolves to a known work and none has been retracted — and get a dated CiteStamped badge you can embed.
See reference health

What this work says

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

inferredcites →https://doi.org/10.1002/asi.22688openalex-snapshot
SciMAT : A new science mapping analysis software tool
inferredcites →https://doi.org/10.1002/rob.21918openalex-snapshot
A survey of deep learning techniques for autonomous driving
inferredcites →https://doi.org/10.1007/978-3-319-99229-7openalex-snapshot
Computer Safety, Reliability, and Security
inferredcites →https://doi.org/10.1007/s00607-021-00953-7openalex-snapshot
Cloud-backed mobile cognition
inferredcites →https://doi.org/10.1007/s11831-021-09670-yopenalex-snapshot
Deep Learning Inspired Object Consolidation Approaches Using LiDAR Data for Autonomous Driving: A Review
inferredcites →https://doi.org/10.1007/s42154-021-00151-3openalex-snapshot
End-to-End Autonomous Driving Through Dueling Double Deep Q-Network
inferredcites →https://doi.org/10.1016/j.atmosenv.2013.04.028openalex-snapshot
Estimation of the contribution of road traffic emissions to particulate matter concentrations from field measurements: A review
inferredcites →https://doi.org/10.1016/j.chemosphere.2021.133082openalex-snapshot
The health effects of traffic-related air pollution: A review focused the health effects of going green
inferredcites →https://doi.org/10.1016/j.emj.2020.04.010openalex-snapshot
What is the future of work? A science mapping analysis
inferredcites →https://doi.org/10.1016/j.iatssr.2019.11.008openalex-snapshot
Deep learning-based image recognition for autonomous driving
inferredcites →https://doi.org/10.1016/j.ijinfomgt.2019.01.013openalex-snapshot
30 years of intelligence models in management and business: A bibliometric review
inferredcites →https://doi.org/10.1016/j.jbusres.2021.04.070openalex-snapshot
How to conduct a bibliometric analysis: An overview and guidelines
inferredcites →https://doi.org/10.1016/j.jclepro.2023.137753openalex-snapshot
Thematic evolution and trends linking sustainability and project management: Scientific mapping using SciMAT
inferredcites →https://doi.org/10.1016/j.knosys.2014.12.035openalex-snapshot
25years at Knowledge-Based Systems: A bibliometric analysis
inferredcites →https://doi.org/10.1016/j.neucom.2021.08.155openalex-snapshot
Deep learning-based perception systems for autonomous driving: A comprehensive survey
inferredcites →https://doi.org/10.1016/j.ssci.2021.105479openalex-snapshot
Deep learning for autonomous vehicle and pedestrian interaction safety
inferredcites →https://doi.org/10.1016/j.vehcom.2019.100184openalex-snapshot
Deep learning models for traffic flow prediction in autonomous vehicles: A review, solutions, and challenges
inferredcites →https://doi.org/10.1038/s42256-020-00237-3openalex-snapshot
Neural circuit policies enabling auditable autonomy
inferredcites →https://doi.org/10.1049/iet-its.2018.5144openalex-snapshot
DeepRange: deep‐learning‐based object detection and ranging in autonomous driving
inferredcites →https://doi.org/10.1080/00140139.2022.2079729openalex-snapshot
Contribution of ergonomics and human factors to sustainable development: a systematic literature review
inferredcites →https://doi.org/10.1080/08839514.2019.1600301openalex-snapshot
Autonomous Vehicles and Embedded Artificial Intelligence: The Challenges of Framing Machine Driving Decisions
inferredcites →https://doi.org/10.1080/21681015.2023.2216701openalex-snapshot
Behind the definition of Industry 5.0: a systematic review of technologies, principles, components, and values
inferredcites →https://doi.org/10.1093/ijlit/eaab002openalex-snapshot
Regulatory approaches to managing artificial intelligence systems in autonomous vehicles in Australia
inferredcites →https://doi.org/10.1108/ijshe-11-2021-0472openalex-snapshot
Classical paradigms versus complexity thinking in engineering education: an essential discussion in the education for sustainable development
inferredcites →https://doi.org/10.1109/access.2020.3012812openalex-snapshot
Link Between Sustainability and Industry 4.0: Trends, Challenges and New Perspectives
inferredcites →https://doi.org/10.1109/access.2022.3144407openalex-snapshot
Autonomous Vehicles Perception (AVP) Using Deep Learning: Modeling, Assessment, and Challenges
inferredcites →https://doi.org/10.1109/access.2022.3222834openalex-snapshot
DeepClean: A Robust Deep Learning Technique for Autonomous Vehicle Camera Data Privacy
inferredcites →https://doi.org/10.1109/csndsp54353.2022.9908023openalex-snapshot
Simulating Malicious Attacks on VANETs for Connected and Autonomous Vehicle Cybersecurity: A Machine Learning Dataset
inferredcites →https://doi.org/10.1109/cvpr.2012.6248074openalex-snapshot
Are we ready for autonomous driving? The KITTI vision benchmark suite
inferredcites →https://doi.org/10.1109/cvpr.2016.91openalex-snapshot
You Only Look Once: Unified, Real-Time Object Detection
inferredcites →https://doi.org/10.1109/cvpr.2017.106openalex-snapshot
Feature Pyramid Networks for Object Detection
inferredcites →https://doi.org/10.1109/iccca49541.2020.9250790openalex-snapshot
Motion Prediction for Autonomous Vehicles from Lyft Dataset using Deep Learning
inferredcites →https://doi.org/10.1109/ijcnn52387.2021.9533808openalex-snapshot
End-to-End Federated Learning for Autonomous Driving Vehicles
inferredcites →https://doi.org/10.1109/intellisys.2017.8324372openalex-snapshot
Machine learning and deep neural network — Artificial intelligence core for lab and real-world test and validation for ADAS and autonomous vehicles: AI for efficient and quality test and validation
inferredcites →https://doi.org/10.1109/iscsic54682.2021.00024openalex-snapshot
Machine Learning Based Dynamic Risk Assessment for Autonomous Vehicles
inferredcites →https://doi.org/10.1109/ivs.2017.7995703openalex-snapshot
Deep learning algorithm for autonomous driving using GoogLeNet
inferredcites →https://doi.org/10.1109/ivs.2017.7995850openalex-snapshot
Feature analysis and selection for training an end-to-end autonomous vehicle controller using deep learning approach
inferredcites →https://doi.org/10.1109/jiot.2020.3048050openalex-snapshot
Deep-Learning-Based Intelligent Intervehicle Distance Control for 6G-Enabled Cooperative Autonomous Driving
inferredcites →https://doi.org/10.1109/lgrs.2020.2993652openalex-snapshot
MiNet: Efficient Deep Learning Automatic Target Recognition for Small Autonomous Vehicles
inferredcites →https://doi.org/10.1109/mci.2019.2901089openalex-snapshot
Reinforcement Learning and Deep Learning Based Lateral Control for Autonomous Driving [Application Notes]
inferredcites →https://doi.org/10.1109/tgcn.2022.3165262openalex-snapshot
Machine Learning-Driven APPs Recommendation for Energy Optimization in Green Communication and Networking for Connected and Autonomous Vehicles
inferredcites →https://doi.org/10.1109/tii.2021.3071405openalex-snapshot
Deep Learning-Based Autonomous Driving Systems: A Survey of Attacks and Defenses
inferredcites →https://doi.org/10.1109/tits.2019.2949915openalex-snapshot
A Systematic Literature Review About the Impact of Artificial Intelligence on Autonomous Vehicle Safety
inferredcites →https://doi.org/10.1109/tits.2020.3002419openalex-snapshot
An Automated Machine Learning (AutoML) Method of Risk Prediction for Decision-Making of Autonomous Vehicles
inferredcites →https://doi.org/10.1109/tits.2020.3009223openalex-snapshot
Deep Learning Based Autonomous Vehicle Super Resolution DOA Estimation for Safety Driving
inferredcites →https://doi.org/10.1109/tits.2020.3012034openalex-snapshot
Deep Learning-Based Vehicle Behavior Prediction for Autonomous Driving Applications: A Review
inferredcites →https://doi.org/10.1109/tits.2020.3023541openalex-snapshot
Deep Learning for Image and Point Cloud Fusion in Autonomous Driving: A Review
inferredcites →https://doi.org/10.1109/tits.2020.3032227openalex-snapshot
Deep Learning for Safe Autonomous Driving: Current Challenges and Future Directions
inferredcites →https://doi.org/10.1109/tits.2020.3042504openalex-snapshot
Deep Learning-Based Traffic Safety Solution for a Mixture of Autonomous and Manual Vehicles in a 5G-Enabled Intelligent Transportation System
inferredcites →https://doi.org/10.1109/tits.2021.3060001openalex-snapshot
Deep Learning-Based Incorporation of Planar Constraints for Robust Stereo Depth Estimation in Autonomous Vehicle Applications
inferredcites →https://doi.org/10.1109/tits.2021.3074695openalex-snapshot
A Survey on Hybrid Human-Artificial Intelligence for Autonomous Driving
inferredcites →https://doi.org/10.1109/tits.2021.3105834openalex-snapshot
An Enhanced Multi-Stage Deep Learning Framework for Detecting Malicious Activities From Autonomous Vehicles
inferredcites →https://doi.org/10.1109/tiv.2022.3185303openalex-snapshot
End-to-End Autonomous Driving With Semantic Depth Cloud Mapping and Multi-Agent
inferredcites →https://doi.org/10.1109/tnnls.2020.3015992openalex-snapshot
Deep Learning for LiDAR Point Clouds in Autonomous Driving: A Review
inferredcites →https://doi.org/10.1109/tnnls.2020.3043505openalex-snapshot
A Survey of End-to-End Driving: Architectures and Training Methods
inferredcites →https://doi.org/10.1109/tpami.2015.2437384openalex-snapshot
Region-Based Convolutional Networks for Accurate Object Detection and Segmentation
inferredcites →https://doi.org/10.1109/tpami.2016.2577031openalex-snapshot
Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks
inferredcites →https://doi.org/10.1109/tpami.2018.2858826openalex-snapshot
Focal Loss for Dense Object Detection
inferredcites →https://doi.org/10.1109/tsmc.2018.2868372openalex-snapshot
Scene Understanding in Deep Learning-Based End-to-End Controllers for Autonomous Vehicles
inferredcites →https://doi.org/10.1109/tvt.2020.2977378openalex-snapshot
Poisoning and Evasion Attacks Against Deep Learning Algorithms in Autonomous Vehicles
inferredcites →https://doi.org/10.1111/1467-8551.00375openalex-snapshot
Towards a Methodology for Developing Evidence‐Informed Management Knowledge by Means of Systematic Review
inferredcites →https://doi.org/10.1111/j.1365-2648.2007.04569.xopenalex-snapshot
The qualitative content analysis process
inferredcites →https://doi.org/10.1136/bmj.n71openalex-snapshot
The PRISMA 2020 statement: an updated guideline for reporting systematic reviews
inferredcites →https://doi.org/10.1145/3065386openalex-snapshot
ImageNet classification with deep convolutional neural networks
inferredcites →https://doi.org/10.1145/3460770openalex-snapshot
Design Guidelines on Deep Learning–based Pedestrian Detection Methods for Supporting Autonomous Vehicles
inferredcites →https://doi.org/10.1155/2019/3737265openalex-snapshot
Deep Learning-Based GNSS Network-Based Real-Time Kinematic Improvement for Autonomous Ground Vehicle Navigation
inferredcites →https://doi.org/10.1155/2022/2938011openalex-snapshot
Application of Machine Learning in Ethical Design of Autonomous Driving Crash Algorithms
inferredcites →https://doi.org/10.1162/qss_a_00019openalex-snapshot
Scopus as a curated, high-quality bibliometric data source for academic research in quantitative science studies
inferredcites →https://doi.org/10.1177/01423312221093147openalex-snapshot
Survey on deep learning-based 3D object detection in autonomous driving
inferredcites →https://doi.org/10.1177/0959651818758865openalex-snapshot
Deep learning–based traffic sign recognition for unmanned autonomous vehicles
inferredcites →https://doi.org/10.22381/crlsj14220225openalex-snapshot
Autonomous Vehicle Ethics in Networked Transport Systems: Spatial Cognition Algorithms, Mobility Data Processing Tools, and Deep Learning-based Sensing Technologies
inferredcites →https://doi.org/10.3390/app11104706openalex-snapshot
Machine Learning Approach to Real-Time 3D Path Planning for Autonomous Navigation of Unmanned Aerial Vehicle
inferredcites →https://doi.org/10.3390/app12146831openalex-snapshot
Vision-Based Autonomous Vehicle Systems Based on Deep Learning: A Systematic Literature Review
inferredcites →https://doi.org/10.3390/electronics11142162openalex-snapshot
A Review on Autonomous Vehicles: Progress, Methods and Challenges
inferredcites →https://doi.org/10.3390/electronics11213551openalex-snapshot
Deep Learning-Based Pedestrian Detection in Autonomous Vehicles: Substantial Issues and Challenges
inferredcites →https://doi.org/10.3390/en14061788openalex-snapshot
An Intelligent Task Scheduling Mechanism for Autonomous Vehicles via Deep Learning
inferredcites →https://doi.org/10.3390/en16073208openalex-snapshot
The Internet of Vehicles and Sustainability—Reflections on Environmental, Social, and Corporate Governance
inferredcites →https://doi.org/10.3390/ijerph18030952openalex-snapshot
A Bibliometric Network Analysis of Coronavirus during the First Eight Months of COVID-19 in 2020
inferredcites →https://doi.org/10.3390/machines5010006openalex-snapshot
Perception, Planning, Control, and Coordination for Autonomous Vehicles
inferredcites →https://doi.org/10.3390/s20154220openalex-snapshot
Deep Learning Sensor Fusion for Autonomous Vehicle Perception and Localization: A Review
inferredcites →https://doi.org/10.7467/ksae.2022.30.8.635openalex-snapshot
A Study on Deep Learning Based Lidar Object Detection Neural Networks for Autonomous Driving

What points at this work

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

inferred← citeshttps://doi.org/10.2139/ssrn.4867975openalex-extracted
Gender Lens Investing: A Bibliometric Analysis
inferred← citeshttps://doi.org/10.1007/s42154-024-00332-wopenalex-snapshot
Recent Advances in Interactive Driving of Autonomous Vehicles: Comprehensive Review of Approaches
inferred← citeshttps://doi.org/10.1016/j.iedeen.2023.100239openalex-snapshot
Evolution of scientific production on urban passenger transport: A bibliometric analysis
inferred← citeshttps://doi.org/10.1016/j.jik.2026.100958openalex-snapshot
A review of gender lens investing: emerging knowledge
inferred← citeshttps://doi.org/10.1016/j.jjimei.2024.100230openalex-snapshot
Impacts of digitization on operational efficiency in the banking sector: Thematic analysis and research agenda proposal
inferred← citeshttps://doi.org/10.1080/09593969.2024.2436841openalex-snapshot
A bibliometric analysis of customer experience in the omni-channel era
inferred← citeshttps://doi.org/10.1109/aimla59606.2024.10531318openalex-snapshot
Connecting Autonomous Engineering Domains with the Shared Language of Deep Neural Networks
inferred← citeshttps://doi.org/10.1109/autocom64127.2025.10957564openalex-snapshot
Unlocking Scholarly Insights Using Deep Learning-Based Evaluation Method for Research Impact Assessment in Academic Institutions
inferred← citeshttps://doi.org/10.1109/icipca65645.2025.11138667openalex-snapshot
Research on Lane Change Decision Models for Autonomous Vehicles Based on Deep Learning
inferred← citeshttps://doi.org/10.1109/smartgencon60755.2023.10441855openalex-snapshot
Retracted: Enabling Autonomous Deep Learning Strategies for Real-Time Data Analysis in Machine Learning
inferred← citeshttps://doi.org/10.1145/3676641.3716265openalex-snapshot
OS2G: A High-Performance DPU Offloading Architecture for GPU-based Deep Learning with Object Storage
inferred← citeshttps://doi.org/10.1177/30504554251325141openalex-snapshot
ELIME: Exact Local Interpretable Model-Agnostic Explanation
inferred← citeshttps://doi.org/10.1515/tw-2025-0019openalex-snapshot
What drives German Gen Z tourists’ intention to use urban on-site autonomous vehicles? An Extended Technology Acceptance Model Study
inferred← citeshttps://doi.org/10.21203/rs.3.rs-10381781/v1openalex-snapshot
A PRISMA-Guided Critical Review of CNN, Transformer, and Hybrid Object Detection Architectures for Autonomous Driving
inferred← citeshttps://doi.org/10.21203/rs.3.rs-8103569/v1openalex-snapshot
STEM Teachers’ Perception of Barriers to Critical Thinking Abilities: Implementing an Integrated Approach in Pakistan’s STEM Education
inferred← citeshttps://doi.org/10.21275/sr24306144435openalex-snapshot
Enhancing Cybersecurity in Cloud - Based Banking - Best Practices and Technologies
inferred← citeshttps://doi.org/10.2339/politeknik.1653494openalex-snapshot
Deniz Üzeri Rüzgâr Enerjisi Bibliyometrik Analizi: Öncelikli Araştırma Alanları ve Gelişen Eğilimler
inferred← citeshttps://doi.org/10.3390/app14073016openalex-snapshot
Advancements in the Intelligent Detection of Driver Fatigue and Distraction: A Comprehensive Review
inferred← citeshttps://doi.org/10.3390/cleantechnol8050139openalex-snapshot
Artificial Intelligence and the Prospects for Net-Zero Energy and Net-Zero Carbon Buildings: A Science Mapping Analysis Using Digital Twins and Geographic Information Systems
inferred← citeshttps://doi.org/10.3390/electronics14214174openalex-snapshot
The Road to Autonomy: A Systematic Review Through AI in Autonomous Vehicles
inferred← citeshttps://doi.org/10.3390/jcm15145482openalex-snapshot
Use of Artificial Intelligence in Rheumatoid Arthritis: Advancements and Novel Perspectives
inferred← citeshttps://doi.org/10.3390/make5040065openalex-snapshot
Brainstorming Will Never Be the Same Again—A Human Group Supported by Artificial Intelligence
inferred← citeshttps://doi.org/10.3390/make8090277openalex-snapshot
A Cross-Layer Review of Intelligent, Secure, and Privacy-Preserving Internet of Vehicles
inferred← citeshttps://doi.org/10.3390/s23177391openalex-snapshot
A Holistic Review of Cyber–Physical–Social Systems: New Directions and Opportunities
inferred← citeshttps://doi.org/10.3390/smartcities8030079openalex-snapshot
A Comprehensive Literature Review on Modular Approaches to Autonomous Driving: Deep Learning for Road and Racing Scenarios
inferred← citeshttps://doi.org/10.4018/979-8-3373-2530-9.ch008openalex-snapshot
Machine Learning for Safer Autonomous Vehicles
inferred← citeshttps://doi.org/10.4018/979-8-3373-8954-7.ch003openalex-snapshot
Intelligent Vibration-Aware Monitoring Systems for Assessing Driver Fatigue and Safety
inferred← citeshttps://doi.org/10.54783/ijsoc.v5i4.826openalex-snapshot
Harnessing the Power of AI in Shaping Administrative Law Regulations
Editorial review for independent work. ICSAC — the Institute for Complexity Science and Advanced Computing — runs a structured editorial panel for researchers publishing outside journals, and publishes on CiteStamp rails. Submission is free and goes through ORCID: icsacinstitute.org/submit.