:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Albaiz, Abdulrahman, Amsaad, Fathi
Format:	Preprint
Published:	2026
Subjects:	Machine Learning
Online Access:	https://arxiv.org/abs/2604.08581
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

K-Means Based TinyML Anomaly Detection and Distributed Model Reuse via the Distributed Internet of Learning (DIoL)
by: Albaiz, Abdulrahman, et al.
Published: (2026)

TinyML for Acoustic Anomaly Detection in IoT Sensor Networks
by: Almaini, Amar, et al.
Published: (2026)

Network Anomaly Detection for IoT Using Hyperdimensional Computing on NSL-KDD
by: Ghajari, Ghazal, et al.
Published: (2025)

Simulating Battery-Powered TinyML Systems Optimised using Reinforcement Learning in Image-Based Anomaly Detection
by: Ping, Jared M., et al.
Published: (2024)

TinyML Security: Exploring Vulnerabilities in Resource-Constrained Machine Learning Systems
by: Huckelberry, Jacob, et al.
Published: (2024)

Benchmarking Energy and Latency in TinyML: A Novel Method for Resource-Constrained AI
by: Bartoli, Pietro, et al.
Published: (2025)

Hybrid Efficient Unsupervised Anomaly Detection for Early Pandemic Case Identification
by: Ghajari, Ghazal, et al.
Published: (2024)

Once-for-All Channel Mixers (HYPERTINYPW): Generative Compression for TinyML
by: Shaalan, Yassien
Published: (2026)

Unsupervised Learning: Comparative Analysis of Clustering Techniques on High-Dimensional Data
by: Baligodugula, Vishnu Vardhan, et al.
Published: (2025)

Pruning-Based TinyML Optimization of Machine Learning Models for Anomaly Detection in Electric Vehicle Charging Infrastructure
by: Dehrouyeh, Fatemeh, et al.
Published: (2025)

TinySV: Speaker Verification in TinyML with On-device Learning
by: Pavan, Massimo, et al.
Published: (2024)

MLonMCU: TinyML Benchmarking with Fast Retargeting
by: van Kempen, Philipp, et al.
Published: (2023)

TinyML-Enabled IoT for Sustainable Precision Irrigation
by: Taueatsoala, Kamogelo, et al.
Published: (2026)

Optimizing the Deployment of Tiny Transformers on Low-Power MCUs
by: Jung, Victor J. B., et al.
Published: (2024)

MicroFlow: An Efficient Rust-Based Inference Engine for TinyML
by: Carnelos, Matteo, et al.
Published: (2024)

Intrusion Detection in IoT Networks Using Hyperdimensional Computing: A Case Study on the NSL-KDD Dataset
by: Ghajari, Ghazal, et al.
Published: (2025)

U-TOE: Universal TinyML On-board Evaluation Toolkit for Low-Power IoT
by: Huang, Zhaolan, et al.
Published: (2023)

Accelerating TinyML Inference on Microcontrollers through Approximate Kernels
by: Armeniakos, Giorgos, et al.
Published: (2024)

Affordable Precision Agriculture: A Deployment-Oriented Review of Low-Cost, Low-Power Edge AI and TinyML for Resource-Constrained Farming Systems
by: Samanta, Riya, et al.
Published: (2026)

Optimizing LoRa for Edge Computing with TinyML Pipeline for Channel Hopping
by: Grunewald, Marla, et al.
Published: (2024)

TinyNav: End-to-End TinyML for Real-Time Autonomous Navigation on Microcontrollers
by: Roy, Pooria, et al.
Published: (2026)

Decentralised Resource Sharing in TinyML: Wireless Bilayer Gossip Parallel SGD for Collaborative Learning
by: Bao, Ziyuan, et al.
Published: (2025)

FERMI-ML: A Flexible and Resource-Efficient Memory-In-Situ SRAM Macro for TinyML acceleration
by: Lokhande, Mukul, et al.
Published: (2025)

Optimizing TinyML: The Impact of Reduced Data Acquisition Rates for Time Series Classification on Microcontrollers
by: Samanta, Riya, et al.
Published: (2024)

Can LLMs Revolutionize the Design of Explainable and Efficient TinyML Models?
by: Zeinaty, Christophe El, et al.
Published: (2025)

Combining Multi-Objective Bayesian Optimization with Reinforcement Learning for TinyML
by: Deutel, Mark, et al.
Published: (2023)

Dendron: Enhancing Human Activity Recognition with On-Device TinyML Learning
by: Shalby, Hazem Hesham Yousef, et al.
Published: (2025)

On The Dynamic Ensemble Selection for TinyML-based Systems -- a Preliminary Study
by: Puslecki, Tobiasz, et al.
Published: (2025)

Hardware-efficient tractable probabilistic inference for TinyML Neurosymbolic AI applications
by: Leslin, Jelin, et al.
Published: (2025)

On-device Online Learning and Semantic Management of TinyML Systems
by: Ren, Haoyu, et al.
Published: (2024)

On TinyML and Cybersecurity: Electric Vehicle Charging Infrastructure Use Case
by: Dehrouyeh, Fatemeh, et al.
Published: (2024)

DTMM: Deploying TinyML Models on Extremely Weak IoT Devices with Pruning
by: Han, Lixiang, et al.
Published: (2024)

Integration of TinyML and LargeML: A Survey of 6G and Beyond
by: Vu, Thai-Hoc, et al.
Published: (2025)

Edge Intelligence for Wildlife Conservation: Real-Time Hornbill Call Classification Using TinyML
by: Hing, Kong Ka, et al.
Published: (2025)

TinyChirp: Bird Song Recognition Using TinyML Models on Low-power Wireless Acoustic Sensors
by: Huang, Zhaolan, et al.
Published: (2024)

Fed-Meta-Align: A Similarity-Aware Aggregation and Personalization Pipeline for Federated TinyML on Heterogeneous Data
by: Macharla, Hemanth, et al.
Published: (2025)

Consolidating TinyML Lifecycle with Large Language Models: Reality, Illusion, or Opportunity?
by: Wu, Guanghan, et al.
Published: (2025)

TinyTNAS: GPU-Free, Time-Bound, Hardware-Aware Neural Architecture Search for TinyML Time Series Classification
by: Saha, Bidyut, et al.
Published: (2024)

A Survey of TinyML Applications in Beekeeping for Hive Monitoring and Management
by: Sucipto, Willy, et al.
Published: (2025)

What changes after deployment? A survey on On-device Learning in TinyML
by: Pavan, Massimo, et al.
Published: (2026)