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ML-MCU: A Framework to Train ML Classifiers on MCU-Based IoT Edge Devices., , и . IEEE Internet Things J., 9 (16): 15007-15017 (2022)Cognitive Digital Twins for Smart Manufacturing., , , , и . IEEE Intell. Syst., 36 (2): 96-100 (2021)A Data-Driven Approach for Building the Profile of Water Storage Capacity of Soils., , , и . Sensors, 23 (12): 5599 (2023)Semantic Modeling, Development and Evaluation for the Resistance Spot Welding Industry., , , , и . IEEE Access, (2023)Semantic Discovery and Integration of Urban Data Streams., , и . S4SC@ISWC, том 1280 из CEUR Workshop Proceedings, стр. 15-30. CEUR-WS.org, (2014)Edge2Train: a framework to train machine learning models (SVMs) on resource-constrained IoT edge devices., , и . IOT, стр. 6:1-6:8. ACM, (2020)RCE-NN: a five-stage pipeline to execute neural networks (CNNs) on resource-constrained IoT edge devices., , и . IOT, стр. 5:1-5:8. ACM, (2020)ElastiCL: Elastic Quantization for Communication Efficient Collaborative Learning in IoT., , , , , , , и . SenSys, стр. 382-383. ACM, (2021)Towards Designing an Explainable-AI based Solution for Livestock Mart Industry., , , , , и . COMAD/CODS, стр. 421. ACM, (2021)Porting and Execution of Anomalies Detection Models on Embedded Systems in IoT: Demo Abstract., , , , , и . IoTDI, стр. 265-266. ACM, (2021)