Thommas K. S. Flores

Orcid: 0000-0003-2808-8529

According to our database1, Thommas K. S. Flores authored at least 25 papers between 2019 and 2026.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book  In proceedings  Article  PhD thesis  Dataset  Other 

Links

Online presence:

On csauthors.net:

Bibliography

2026
Evolving vector quantization-aware training: an adaptive method for compressing machine learning models.
Evol. Syst., June, 2026

On the role of AI in building generative urban intelligence.
Artif. Intell. Rev., February, 2026

2025
TensorFlores: An enhanced Python-based TinyML framework.
SoftwareX, 2025

Advancing Tiny Machine Learning Operations: Robust Model Updates in the Internet of Intelligent Vehicles.
IEEE Micro, 2025

Enhanced Vector Quantization for Embedded Machine Learning: A Post-Training Approach With Incremental Clustering.
IEEE Access, 2025

Quantifying the Carbon Footprint of Electric Vehicles in Sustainable Urban Mobility.
Proceedings of the IEEE International Smart Cities Conference, 2025

Dependability-Driven Planning of Wireless Sensor Networks for Smart Cities Using Machine Learning.
Proceedings of the 51st Annual Conference of the IEEE Industrial Electronics Society, 2025

Embedded AI for Intelligent Wildfire Monitoring: A Multi-Sensor and Vision-Driven Approach.
Proceedings of the 51st Annual Conference of the IEEE Industrial Electronics Society, 2025

Kolmogorov-Arnold Networks under TinyML Constraints: A Study on SoC Estimation for Electric Vehicles.
Proceedings of the 30th IEEE International Conference on Emerging Technologies and Factory Automation, 2025

2024
Online Processing of Vehicular Data on the Edge Through an Unsupervised TinyML Regression Technique.
ACM Trans. Embed. Comput. Syst., May, 2024

TinyML Implementation and Optimization for Fuel Type Classification on OBD-II Edge Device.
Proceedings of the Symposium on Internet of Things, 2024

A Multi-Layered Methodology for Driver Behavior Analysis Using TinyML and Edge Computing.
Proceedings of the IEEE International Conference on Evolving and Adaptive Intelligent Systems, 2024

2023
Leveraging IoT and TinyML for Smart Battery Management in Electric Bicycles.
Proceedings of the Symposium on Internet of Things, 2023

Can adaptive strategies sustain bidirectional LoRaWAN traffic?
Proceedings of the 2023 IEEE International Workshop on Metrology for Industry 4.0 & IoT, 2023

TinyML for Safe Driving: The Use of Embedded Machine Learning for Detecting Driver Distraction.
Proceedings of the IEEE International Workshop on Metrology for Automotive, 2023

TinyML-Based Pothole Detection: A Comparative Analysis of YOLO and FOMO Model Performance.
Proceedings of the IEEE Latin American Conference on Computational Intelligence, 2023

2022
State of Charge Estimation of Battery Based on Neural Networks and Adaptive Strategies with Correntropy.
Sensors, 2022

Development of a Soft Sensor for Flow Estimation in Water Supply Systems Using Artificial Neural Networks.
Sensors, 2022

A TinyML Soft-Sensor Approach for Low-Cost Detection and Monitoring of Vehicular Emissions.
Sensors, 2022

A data-stream TinyML compression algorithm for vehicular applications: a case study.
Proceedings of the IEEE International Workshop on Metrology for Industry 4.0 & IoT, 2022

A TinyML Soft-Sensor for the Internet of Intelligent Vehicles.
Proceedings of the IEEE International Workshop on Metrology for Automotive, 2022

An Online Unsupervised Machine Learning Approach to Detect Driving Related Events.
Proceedings of the IECON 2022, 2022

2021
Adaptive Pressure Control System Based on the Maximum Correntropy Criterion.
Sensors, 2021

Indirect Feedback Measurement of Flow in a Water Pumping Network Employing Artificial Intelligence.
Sensors, 2021

2019
Fuzzy Pressure Control System in Water Supply Networks with Series-Parallel Pumps.
Proceedings of the IEEE International Instrumentation and Measurement Technology Conference, 2019


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