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ML-MCU: A Framework to Train ML Classifiers on MCU-Based IoT Edge Devices., , and . IEEE Internet Things J., 9 (16): 15007-15017 (2022)Semantic Modeling, Development and Evaluation for the Resistance Spot Welding Industry., , , , and . IEEE Access, (2023)Globe2Train: A Framework for Distributed ML Model Training using IoT Devices Across the Globe., , and . SmartWorld/SCALCOM/UIC/ATC/IOP/SCI, page 107-114. IEEE, (2021)Train++: An Incremental ML Model Training Algorithm to Create Self-Learning IoT Devices., , , and . SmartWorld/SCALCOM/UIC/ATC/IOP/SCI, page 97-106. IEEE, (2021)Edge2Train: a framework to train machine learning models (SVMs) on resource-constrained IoT edge devices., , and . IOT, page 6:1-6:8. ACM, (2020)RCE-NN: a five-stage pipeline to execute neural networks (CNNs) on resource-constrained IoT edge devices., , and . IOT, page 5:1-5:8. ACM, (2020)ElastiCL: Elastic Quantization for Communication Efficient Collaborative Learning in IoT., , , , , , , and . SenSys, page 382-383. ACM, (2021)A Data-Driven Approach for Building the Profile of Water Storage Capacity of Soils., , , and . Sensors, 23 (12): 5599 (2023)Towards Designing an Explainable-AI based Solution for Livestock Mart Industry., , , , , and . COMAD/CODS, page 421. ACM, (2021)An SRAM Optimized Approach for Constant Memory Consumption and Ultra-fast Execution of ML Classifiers on TinyML Hardware., , , and . SCC, page 319-328. IEEE, (2021)