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Machine Learning in Resource-Scarce Embedded Systems, FPGAs, and End-Devices: A Survey

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What this work says

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

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Fundamentals of RTOS-Based Digital Controller Implementation
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Data Analysis, Machine Learning and Applications
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KNIME: The Konstanz Information Miner
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Handbook of Networked and Embedded Control Systems
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Optimizing database architecture for the new bottleneck: memory access
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Elasticity in cloud computing: a survey
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Operating systems for low-end smart devices: a survey and a proposed solution framework
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The WEKA workbench
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Wireless sensor networks for healthcare: A survey
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Machine learning for internet of things data analysis: a survey
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Machine learning algorithms for wireless sensor networks: A survey
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Industry 4.0: A survey on technologies, applications and open research issues
inferredcites →https://doi.org/10.1016/j.mfglet.2018.01.005openalex-snapshot
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inferredcites →https://doi.org/10.1016/j.patrec.2005.10.010openalex-snapshot
An introduction to ROC analysis
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No free lunch theorems for optimization
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A Review of Low-End, Middle-End, and High-End Iot Devices
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A Survey of Machine Learning Techniques Applied to Self-Organizing Cellular Networks
inferredcites →https://doi.org/10.1109/comst.2017.2782666openalex-snapshot
Survey and Taxonomy of Transmissions Power Control Mechanisms for Wireless Body Area Networks
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Deep Learning for IoT Big Data and Streaming Analytics: A Survey
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Deep Learning in Mobile and Wireless Networking: A Survey
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A Survey of Machine and Deep Learning Methods for Internet of Things (IoT) Security
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Efficient Compute at the Edge: Optimizing Energy Aware Data Structures for Emerging Edge Hardware
inferredcites →https://doi.org/10.1109/iccsee.2012.193openalex-snapshot
Data Security and Privacy Protection Issues in Cloud Computing
inferredcites →https://doi.org/10.1109/icdcs.2017.226openalex-snapshot
Distributed Deep Neural Networks Over the Cloud, the Edge and End Devices
inferredcites →https://doi.org/10.1109/iembs.2009.5333790openalex-snapshot
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inferredcites →https://doi.org/10.1109/iisa.2017.8316459openalex-snapshot
A brief survey of machine learning methods and their sensor and IoT applications
inferredcites →https://doi.org/10.1109/ijcnn.2016.7727200openalex-snapshot
Distributed neural network: Dynamic learning via backpropagation with hardware neurons using arduino chips
inferredcites →https://doi.org/10.1109/infocom.2018.8486403openalex-snapshot
When Edge Meets Learning: Adaptive Control for Resource-Constrained Distributed Machine Learning
inferredcites →https://doi.org/10.1109/itsim.2008.4631872openalex-snapshot
Fairness and interactive performance of O(1) and CFS Linux kernel schedulers
inferredcites →https://doi.org/10.1109/jsac.2009.090105openalex-snapshot
Transmission Power Control in Body Area Sensor Networks for Healthcare Monitoring
inferredcites →https://doi.org/10.1109/jssc.2013.2253226openalex-snapshot
A Low-Power Processor With Configurable Embedded Machine-Learning Accelerators for High-Order and Adaptive Analysis of Medical-Sensor Signals
inferredcites →https://doi.org/10.1109/mc.2018.2381119openalex-snapshot
Breathing-Based Authentication on Resource-Constrained IoT Devices using Recurrent Neural Networks
inferredcites →https://doi.org/10.1109/mcc.2014.20openalex-snapshot
Security and Privacy in Cloud Computing
inferredcites →https://doi.org/10.1109/mcom.2012.6384464openalex-snapshot
Management of resource constrained devices in the internet of things
inferredcites →https://doi.org/10.1109/mis.2009.36openalex-snapshot
The Unreasonable Effectiveness of Data
inferredcites →https://doi.org/10.1109/mnet.2018.1700202openalex-snapshot
Learning IoT in Edge: Deep Learning for the Internet of Things with Edge Computing
inferredcites →https://doi.org/10.1109/mssc.2017.2745818openalex-snapshot
Embedded Deep Neural Network Processing: Algorithmic and Processor Techniques Bring Deep Learning to IoT and Edge Devices
inferredcites →https://doi.org/10.1109/mvt.2011.941888openalex-snapshot
Microcontroller Units in Automobiles [Automotive Electronics]
inferredcites →https://doi.org/10.1109/percomw.2019.8730784openalex-snapshot
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inferredcites →https://doi.org/10.1109/pimrc.2011.6139908openalex-snapshot
Dynamic power control in Wireless Body Area Networks using reinforcement learning with approximation
inferredcites →https://doi.org/10.1109/sas.2017.7894091openalex-snapshot
Real-time room occupancy estimation with Bayesian machine learning using a single PIR sensor and microcontroller
inferredcites →https://doi.org/10.1109/sbesc.2018.00036openalex-snapshot
Intrusion Detection via MLP Neural Network Using an Arduino Embedded System
inferredcites →https://doi.org/10.1109/tdmr.2005.858914openalex-snapshot
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inferredcites →https://doi.org/10.1109/tii.2018.2855198openalex-snapshot
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inferredcites →https://doi.org/10.1109/tit.1967.1053964openalex-snapshot
Nearest neighbor pattern classification
inferredcites →https://doi.org/10.1109/wf-iot.2018.8355177openalex-snapshot
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inferredcites →https://doi.org/10.1115/1.4004223openalex-snapshot
Toward a Better Understanding of Model Validation Metrics
inferredcites →https://doi.org/10.1137/141000671openalex-snapshot
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inferredcites →https://doi.org/10.1145/103162.103163openalex-snapshot
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inferredcites →https://doi.org/10.1145/1150402.1150464openalex-snapshot
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inferredcites →https://doi.org/10.1145/130385.130401openalex-snapshot
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inferredcites →https://doi.org/10.1145/1961189.1961199openalex-snapshot
LIBSVM
inferredcites →https://doi.org/10.1145/2347736.2347755openalex-snapshot
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inferredcites →https://doi.org/10.1145/2647868.2654889openalex-snapshot
Caffe
inferredcites →https://doi.org/10.1145/3297858.3304011openalex-snapshot
Intelligence Beyond the Edge
inferredcites →https://doi.org/10.1145/3314221.3314597openalex-snapshot
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inferredcites →https://doi.org/10.1145/356887.356892openalex-snapshot
Cache Memories
inferredcites →https://doi.org/10.1145/357783.331677openalex-snapshot
The processor-memory bottleneck
inferredcites →https://doi.org/10.1155/2013/324641openalex-snapshot
Providing Virtual Memory Support for Sensor Networks with Mass Data Processing
inferredcites →https://doi.org/10.1155/2018/1068261openalex-snapshot
Software‐Defined Virtual Testbed for IoT Systems
inferredcites →https://doi.org/10.1162/neco.1996.8.7.1341openalex-snapshot
The Lack of A Priori Distinctions Between Learning Algorithms
inferredcites →https://doi.org/10.1609/aimag.v26i4.1848openalex-snapshot
A (Very) Brief History of Artificial Intelligence
inferredcites →https://doi.org/10.1613/jair.301openalex-snapshot
Reinforcement Learning: A Survey
inferredcites →https://doi.org/10.23919/date.2018.8342120openalex-snapshot
An overview of next-generation architectures for machine learning: Roadmap, opportunities and challenges in the IoT era
inferredcites →https://doi.org/10.3115/1073012.1073017openalex-snapshot
Scaling to very very large corpora for natural language disambiguation
inferredcites →https://doi.org/10.3115/v1/d14-1179openalex-snapshot
Learning Phrase Representations using RNN Encoder–Decoder for Statistical Machine Translation
inferredcites →https://doi.org/10.3390/fi10030024openalex-snapshot
How Data Will Transform Industrial Processes: Crowdsensing, Crowdsourcing and Big Data as Pillars of Industry 4.0
inferredcites →https://doi.org/10.3390/s150409277openalex-snapshot
Online Learning Algorithm for Time Series Forecasting Suitable for Low Cost Wireless Sensor Networks Nodes
inferredcites →https://doi.org/10.3390/s16060890openalex-snapshot
RF Path and Absorption Loss Estimation for Underwater Wireless Sensor Networks in Different Water Environments
inferredcites →https://doi.org/10.3390/s19010015openalex-snapshot
Clock Frequency Impact on the Performance of High-Security Cryptographic Cipher Suites for Energy-Efficient Resource-Constrained IoT Devices
inferredcites →https://doi.org/10.48550/arxiv.1201.0490openalex-snapshot
Scikit-learn: Machine Learning in Python
inferredcites →https://doi.org/10.48550/arxiv.1406.1078openalex-snapshot
Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translation
inferredcites →https://doi.org/10.48550/arxiv.1408.5093openalex-snapshot
Caffe: Convolutional Architecture for Fast Feature Embedding
inferredcites →https://doi.org/10.48550/arxiv.1511.06393openalex-snapshot
Fixed Point Quantization of Deep Convolutional Networks
inferredcites →https://doi.org/10.48550/arxiv.1805.09473openalex-snapshot
Deploy Large-Scale Deep Neural Networks in Resource Constrained IoT Devices with Local Quantization Region
inferredcites →https://doi.org/10.5555/944919.944968openalex-snapshot
An introduction to variable and feature selection
inferredcites →https://doi.org/10.5860/choice.194685openalex-snapshot
The master algorithm: how the quest for the ultimate learning machine will remake our world
inferredcites →https://doi.org/10.6028/nist.sp.800-145openalex-snapshot
The NIST definition of cloud computing

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

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inferred← citeshttps://doi.org/10.1007/978-981-96-8935-4_5openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/978-981-97-6222-4_27openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/s10489-024-05573-0openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/s10618-023-00921-zopenalex-snapshot
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inferred← citeshttps://doi.org/10.1007/s10994-025-06866-2openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.arcontrol.2026.101055openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.array.2026.100746openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.asoc.2026.116615openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.cag.2024.104015openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.cose.2024.103786openalex-snapshot
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inferred← citeshttps://doi.org/10.1515/jisys-2020-0150openalex-snapshot
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inferred← citeshttps://doi.org/10.24963/ijcai.2022/555openalex-snapshot
TinyLight: Adaptive Traffic Signal Control on Devices with Extremely Limited Resources
inferred← citeshttps://doi.org/10.30572/2018/kje/150309openalex-snapshot
OBJECT DETECTION ALGORITHMS IMPLEMENTATION ON EMBEDDED DEVICES: CHALLENGES AND SUGGESTED SOLUTIONS
inferred← citeshttps://doi.org/10.3389/fnins.2022.999029openalex-snapshot
Spike encoding techniques for IoT time-varying signals benchmarked on a neuromorphic classification task
inferred← citeshttps://doi.org/10.3389/fphy.2024.1285854openalex-snapshot
Data reduction and processing for photon science detectors
inferred← citeshttps://doi.org/10.3390/bios11100366openalex-snapshot
An FPGA-Based Machine Learning Tool for In-Situ Food Quality Tracking Using Sensor Fusion
inferred← citeshttps://doi.org/10.3390/bios11100372openalex-snapshot
Recent Advances on IoT-Assisted Wearable Sensor Systems for Healthcare Monitoring
inferred← citeshttps://doi.org/10.3390/computers12060110openalex-snapshot
Persistence Landscapes—Implementing a Dataset Verification Method in Resource-Scarce Embedded Systems
inferred← citeshttps://doi.org/10.3390/electronics10060689openalex-snapshot
On-Device Deep Learning Inference for System-on-Chip (SoC) Architectures
inferred← citeshttps://doi.org/10.3390/electronics10080901openalex-snapshot
Improving Characteristics of LUT-Based Mealy FSMs with Twofold State Assignment
inferred← citeshttps://doi.org/10.3390/electronics13091624openalex-snapshot
CBin-NN: An Inference Engine for Binarized Neural Networks
inferred← citeshttps://doi.org/10.3390/electronics9111859openalex-snapshot
Improving the Characteristics of Multi-Level LUT-Based Mealy FSMs
inferred← citeshttps://doi.org/10.3390/en14206636openalex-snapshot
Self-Learning Pipeline for Low-Energy Resource-Constrained Devices
inferred← citeshttps://doi.org/10.3390/jimaging8120326openalex-snapshot
Embedded Vision Intelligence for the Safety of Smart Cities
inferred← citeshttps://doi.org/10.3390/jsan10040060openalex-snapshot
Trends in Intelligent Communication Systems: Review of Standards, Major Research Projects, and Identification of Research Gaps
inferred← citeshttps://doi.org/10.3390/math11112561openalex-snapshot
Mobile Robot Navigation Based on Embedded Computer Vision
inferred← citeshttps://doi.org/10.3390/s21134412openalex-snapshot
An Overview of Machine Learning within Embedded and Mobile Devices–Optimizations and Applications
inferred← citeshttps://doi.org/10.3390/s22103657openalex-snapshot
0-Dimensional Persistent Homology Analysis Implementation in Resource-Scarce Embedded Systems
inferred← citeshttps://doi.org/10.3390/s22114205openalex-snapshot
Benchmarking Object Detection Deep Learning Models in Embedded Devices
inferred← citeshttps://doi.org/10.3390/s24185965openalex-snapshot
Image Processing for Smart Agriculture Applications Using Cloud-Fog Computing
inferred← citeshttps://doi.org/10.3390/s24237709openalex-snapshot
FPGA-Based Sensors for Distributed Digital Manufacturing Systems: A State-of-the-Art Review
inferred← citeshttps://doi.org/10.3390/sym18071220openalex-snapshot
Edge-Intelligent Industrial Inspection: A GPU-Accelerated Multiscale CNN Framework for Real-Time Visual Quality Assessment
inferred← citeshttps://doi.org/10.3390/wevj16040236openalex-snapshot
Compensating PI Controller’s Transients with Tiny Neural Network for Vector Control of Permanent Magnet Synchronous Motors
inferred← citeshttps://doi.org/10.36227/techrxiv.171198181.15924940/v1openalex-snapshot
Machine-Learning Health Monitoring System for Resource-Scarce Embedded Systems
inferred← citeshttps://doi.org/10.36227/techrxiv.21405120openalex-snapshot
Cached Machine Learning - A Local Caching System to Reduce Cloud-Communication Dependency During Inference Phase
inferred← citeshttps://doi.org/10.36227/techrxiv.21405120.v1openalex-snapshot
Cached Machine Learning - A Local Caching System to Reduce Cloud-Communication Dependency During Inference Phase
inferred← citeshttps://doi.org/10.37391/ijeer.100254openalex-snapshot
A Classy Memory Management System (CyM2S) using an Isolated Dynamic Two-Level Memory Allocation (ID2LMA) Algorithm for the Real Time Embedded Systems
inferred← citeshttps://doi.org/10.4018/ijtd.300744openalex-snapshot
Embedded Systems Design Space Exploration Under Security Constraints
inferred← citeshttps://doi.org/10.48550/arxiv.2312.02739openalex-snapshot
LExCI: A Framework for Reinforcement Learning with Embedded Systems
inferred← citeshttps://doi.org/10.5753/jbcs.2025.4210openalex-snapshot
Environmental Monitoring with Low-Processing Embedded AI through Sound Event Classification
inferred← citeshttps://doi.org/10.70675/b7632edfz3807z4b8fzb462z31a6dcf54161openalex-snapshot
Design of mixed system (RRAM memory & digital) targeting binary neural network hardware accelerator
inferred← citeshttps://doi.org/10.70675/c2343605zad4cz4066za4ddzd09f55cbf578openalex-snapshot
Management des performances de sûreté et de sécurité pour les applications automotives et IoT
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