Tiny ML

ML: Machine Learning

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Overview

TinyML studies how to run useful machine-learning tasks directly on microcontrollers and other resource-constrained edge devices, often without reliable connectivity. Common approaches include quantization, pruning, distillation, compact architectures, hardware-aware neural architecture search, and efficient feature extraction, with designs measured for latency, memory, and energy on target hardware. Applications include audio and gesture recognition, anomaly detection, embedded vision, and autonomous control, where local processing can reduce communication needs and support timely responses. The central challenge is balancing accuracy and robustness against hardware limits, while making benchmarks reflect real devices, data shifts, and deployment conditions.

Latest papers

CardsList

49 papers1 paper in the last four weeks, down 80% on the four weeks before. 0.0% of all new papers.

  1. SincDPNet: Interpretable Raw-Waveform Bathroom Activity Recognition for Assistive Living

    Sep 28, 2026Debolina Chowdhury, Suman Samui, Sujoy SahaTiny MLSound Event Detection

    Department of Computer Science and Engineering, National Institute of Technology Durgapur, Durgapur 713209, West Bengal, India · Department of Electronics and Communication Engineering, National Institute of Technology Durgapur, Durgapur 713209, West Bengal, India

  2. Rank-Reliable Teacher-Guided Fitness Approximation for Expensive Evolutionary Optimization: A TinyML Architecture Search Study

    Sep 24, 2026Soumen Garai, Suman SamuiNeural Architecture SearchMulti-Fidelity Optimization

    Department of Electronics and Communication Engineering, National Institute of Technology Durgapur, West Bengal 713209, India

  3. A Rapid Pipeline for Training and Deploying ML Models on WeBe Band

    Sep 24, 2026Ehsan Kourkchi, Asmita Asmita, Houman Homayoun +1Tiny MLEdge ML

    Dep. of Electrical and Computer Engineering UC Davis, CA, USA. · dept. name of organization (of Aff.) Quandary Peak Research Los Angeles, CA, USA.

  4. When Labels Are Scarce: An Oscillatory State Space Model for Vibration Diagnosis

    Sep 23, 2026Mainak Mallick, Seung-Kyum ChoiPredictive MaintenanceTiny ML

    Georgia Institute of Technology

  5. Reliable Federated TinyML Deployment for IoT Security

    Sep 23, 2026Younsoo Park, Seokhyoen Bae, Shasi Kumar Ramachandran Prabhu +2IoT Intrusion DetectionTiny ML

    The Pennsylvania State University, University Park, Pennsylvania, USA · Elizabethtown College, Elizabethtown, Pennsylvania, USA

  6. Adaptive AI: Energy Efficient Multi-exit TinyML on Intelligent Vision Systems at the Edge

    Sep 14, 2026Luca Crupi, Lorenzo Lamberti, Alessandro Giusti +1Efficient Neural Network InferenceEnergy-Efficient ML

    IDSIA, SUPSI, Lugano, Switzerland · IIS, ETH Zürich, Switzerland

  7. On the Instance Hardness as a Decision Criterion in TinyML Systems

    Aug 30, 2026Tobiasz Puslecki, Krzysztof WalkowiakEnergy-Efficient MLInference-Time Optimization

    Department of Systems and Computer Networks, Wroclaw University of Science and Technology

  8. PolyChirp: Multi-Species Birdsong Classification Using TinyML on Low-Power Acoustic Sensors

    Aug 24, 2026Nathan Duboisset, Zhaolan Huang, Felix Bießmann +3Bird Vocalization ClassificationAudio Classification

    Ecole Polytechnique, Palaiseau, France · Freie Universität Berlin, Berlin, Germany · Berlin University of Applied Sciences (BHT), Berlin, Germany +2

  9. Enhancing Multiclass Malware Classification in Resource-Constrained Environments

    Aug 23, 2026Abdul Khalek Alve, Alif Rahman, Saadman Zaman +2Malware ClassificationMalware Detection

    Department of Computer Science and Engineering BRAC University, Dhaka, Bangladesh

  10. Power-Performance Characterization of TinyML Systems

    Aug 21, 2026Yujie Zhang, Dhananjaya Wijerathne, Zhaoying Li +1Tiny MLEnergy-Efficient ML

    School of Computing, National University of Singapore

  11. A Real-Time Tsetlin Machine-based Non-intrusive Load Monitoring System on MCUs

    Aug 19, 2026Han Wu, Tianhang Tan, Shengyu Duan +3Non-Intrusive Load MonitoringOn-Device Inference

    School of Engineering, Newcastle University, Newcastle upon Tyne, United Kingdom

  12. A Multiplication-Free Feature Extractor for Signal Classification: Keyword Spotting Case Study

    Aug 17, 2026Radu Dogaru, Ioana DogaruSpeech ProcessingTiny ML

    Dept. of Applied Electronics and Information Engineering, National University of Science and Technology POLITEHNICA Bucharest, Romania

  13. TinyCast: Probabilistic Zero-Shot Forecasting with Computed Periodicity

    Aug 16, 2026Armin SteinhauserZero-Shot Time Series ForecastingProbabilistic Time Series Forecasting

    RAWS Labs

  14. NPLSD: Accelerating Line-Segment Detection on NPU Microcontrollers

    Aug 12, 2026Parsa Hassani Shariat Panahi, Amir Hossein Jalilvand, M. Hassan NajafiEdge InferenceEfficient Neural Network Inference

    School of Computer Engineering, Iran University of Science and Technology, Tehran, Iran · Electrical, Computer, and Systems Engineering Department, Case Western Reserve University, Cleveland, OH, USA

  15. ENAS: An Efficient Hardware-Aware Neural Architecture Search Framework for TinyML on Resource-Constrained Microcontrollers

    Aug 10, 2026Mohd Moin Khan, Naman Srivastava, Pandarasamy ArjunanHardware-Aware NASNeural Architecture Search

    Indian Institute of Science (IISc), Bengaluru 560012, India

  16. Human-Centered Explainable AI for TinyML Edge Devices: A Pareto-Based Selection Framework with LLM-Guided Design

    Aug 7, 2026Zeinab Dehghani, Dhavalkumar Thakker, Koorosh Aslansefat +4Explainable Artificial IntelligenceTiny ML

    School of Digital and Physical Sciences, University of Hull, Cottingham Road, Hull, HU6 7RX, United Kingdom

  17. Scalable Keyword Spotting via Modular Network Expansion

    Jul 22, 2026Viktor Khaymonenko, Dzmitry Saladukha, Aliaksei Rak +1Class-Incremental LearningEfficient Neural Network Inference

    Embedded Voice Input Team, Yandex, Russia · Embedded Voice Input Team, Yandex, Belarus

  18. Ultra-Compact CNN Architectures for Tropical Bird Audio Detection on Microcontrollers

    Jul 22, 2026Muhammad Mun'im Ahmad Zabidi, Mohd Yamani Idna Idris, Norisma IdrisConvolutional Neural NetworksWildlife Monitoring

    Faculty of Computer Science and Information Technology, Universiti Malaya, Kuala Lumpur, Malaysia

  19. Improving Autonomous Nano-drones Performance via Automated End-to-End Optimization and Deployment of DNNs

    Jul 14, 2026Vlad Niculescu, Lorenzo Lamberti, Francesco Conti +2Efficient Neural Network InferenceAerial Robotics

    Integrated Systems Laboratory - ETH Zürich, Switzerland · Department of Electrical, Electronic and Information Engineering - University of Bologna, Italy · Dalle Molle Institute for Artificial Intelligence - USI-SUPSI, Switzerland

  20. Low-Power License Plate Detection and Recognition on a RISC-V Multi-Core MCU-Based Vision System

    Jul 7, 2026Lorenzo Lamberti, Manuele Rusci, Marco Fariselli +2Energy-Efficient MLTiny ML

    Department of Electrical, Electronic and Information Engineering - University of Bologna, Italy · GreenWaves Technologies, Grenoble, France · Integrated System Laboratory - ETH Zurich, Switzerland

  21. MiLSD: A Micro Line-Segment Detector for Resource-Constrained Devices

    Jul 7, 2026Parsa Hassani Shariat Panahi, Amir Hossein Jalilvand, M. Hassan NajafiTiny MLMemory-Efficient Inference

    School of Computer Engineering, Iran University of Science and Technology, Tehran, Iran · Electrical, Computer, and Systems Engineering Department, Case Western Reserve University, OH, USA

  22. Embedded Machine Learning for Microcontroller-Class Edge Devices: Data, Feature, Evaluation, and Deployment Pipelines

    Jun 16, 2026Mostafa DarvishiEfficient Neural Network InferenceKeyword Spotting

  23. An affordable hardware-aware neural architecture search for deploying convolutional neural networks on ultra-low-power computing platforms

    Jun 15, 2026Andrea Mattia Garavagno, Edoardo Ragusa, Antonio Frisoli +1Efficient Neural Network InferenceTiny ML

    Dept. of Electrical, Electronic, Telecommunications Engineering and Naval Architecture (DITEN), University of Genoa, Genoa, Italy · Department of Excellence in Robotics & AI and Institute of Mechanical Intelligence, Scuola Superiore Sant’Anna, 56127 Pisa, Italy

  24. Embedded Arena: Iterative Optimization via Hardware Feedback

    Jun 15, 2026Zhihan Zhang, Alexander Le Metzger, Jiuyang Lyu +10Large Language Model-Guided OptimizationTiny ML

    University of Washington · University of California San Diego · Northeastern University

  25. TinyML-Driven Cybersecurity for Autonomous Spacecraft: Latency-Accuracy Analysis for SPARTA RF and Cyber Threat Detection

    Jun 4, 2026Van Le, Trevor Tran, Tan LeAutonomous Cyber DefenseCybersecurity

    Virginia Tech, Blacksburg, VA 24061, USA · Hampton University, Hampton, VA 23669, USA

  26. What changes after deployment? A survey on On-device Learning in TinyML

    May 29, 2026Massimo Pavan, Luca Pezzarossa, Fabrizio Pittorino +2On-Device TrainingDistribution Shift

    Technical University of Denmark (DTU), Kongens Lyngby, Denmark · Politecnico di Milano, Milan, Italy

  27. FTerViT: Fully Ternary Vision Transformer

    May 20, 2026Szymon Ruciński, Pietro Bonazzi, Engin Türetken +3Ternary QuantizationVision Transformer

    CSEM, Neuchâtel, Switzerland · ETH Zürich, Zurich, Switzerland

  28. Efficient Sensor Fusion for Gesture Recognition on Resource-Constrained Devices

    May 13, 2026Pietro Bartoli, Christian Veronesi, Tommaso Bondini +2Human Activity RecognitionTiny ML

    Dipartimento di Elettronica, Informazione e Bioingegneria (DEIB) Politecnico di Milano, Milan, Italy

  29. TinySSL: Distilled Self-Supervised Pretraining for Sub-Megabyte MCU Models

    May 7, 2026Bibin WilsonSelf-Supervised LearningSelf-Supervised Pre-Training

  30. On-Device Vision Training, Deployment, and Inference on a Thumb-Sized Microcontroller

    Apr 24, 2026Jeremy EllisOn-Device TrainingTiny ML

    High School Robotics Educator, British Columbia, Canada