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20232026
most citedPredictive Maintenance Model Based on Anomaly Detection in Induction Motors: A Machine Learning Approach Using Real-Time IoT Data

20 citations · 21 across the 5 of their papers we have counts for

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cs.LG2026

BranchShine: Compact Raw-Audio-to-IPA Transcription with a RoPE E-Branchformer Encoder

Nikhil Navas, Sergio Chevtchenko, Talisson Damiao +1

Speech-to-IPA transcription is useful when the desired output is pronunciation rather than orthographic text, but competitive multilingual systems are often large and evaluation is…

cs.LG2025

An End-to-End Approach for Child Reading Assessment in the Xhosa Language

Sergio Chevtchenko, Nikhil Navas, Rafaella Vale +6

Child literacy is a strong predictor of life outcomes at the subsequent stages of an individual's life. This points to a need for targeted interventions in vulnerable low and middl…

cs.LG202320 cited

Predictive Maintenance Model Based on Anomaly Detection in Induction Motors: A Machine Learning Approach Using Real-Time IoT Data

Sergio F. Chevtchenko, Monalisa C. M. dos Santos, Diego M. Vieira +5

With the support of Internet of Things (IoT) devices, it is possible to acquire data from degradation phenomena and design data-driven models to perform anomaly detection in indust…

cs.LG2023

A Mapping Study of Machine Learning Methods for Remaining Useful Life Estimation of Lead-Acid Batteries

Sérgio F Chevtchenko, Elisson da Silva Rocha, Bruna Cruz +2

Energy storage solutions play an increasingly important role in modern infrastructure and lead-acid batteries are among the most commonly used in the rechargeable category. Due to…

cs.LG2023

Anomaly Detection in Industrial Machinery using IoT Devices and Machine Learning: a Systematic Mapping

Sérgio F. Chevtchenko, Elisson da Silva Rocha, Monalisa Cristina Moura Dos Santos +4

Anomaly detection is critical in the smart industry for preventing equipment failure, reducing downtime, and improving safety. Internet of Things (IoT) has enabled the collection o…