16 citations · 48 across the 9 of their papers we have counts for
9 papers
LD-RPMNet: Near-Sensor Diagnosis for Railway Point Machines
Wei Li, Xiaochun Wu, Xiaoxi Hu +3
Near-sensor diagnosis has become increasingly prevalent in industry. This study proposes a lightweight model named LD-RPMNet that integrates Transformers and Convolutional Neural N…
On-Device Crack Segmentation for Edge Structural Health Monitoring
Yuxuan Zhang, Ye Xu, Luciano Sebastian Martinez-Rau +3
Crack segmentation can play a critical role in Structural Health Monitoring (SHM) by enabling accurate identification of crack size and location, which allows to monitor structural…
Efficient Continual Learning in Keyword Spotting using Binary Neural Networks
Quynh Nguyen-Phuong Vu, Luciano Sebastian Martinez-Rau, Yuxuan Zhang +4
Keyword spotting (KWS) is an essential function that enables interaction with ubiquitous smart devices. However, in resource-limited devices, KWS models are often static and can th…
Adaptive Noise Resilient Keyword Spotting Using One-Shot Learning
Luciano Sebastian Martinez-Rau, Quynh Nguyen Phuong Vu, Yuxuan Zhang +2
Keyword spotting (KWS) is a key component of smart devices, enabling efficient and intuitive audio interaction. However, standard KWS systems deployed on embedded devices often suf…
Survey of Quantization Techniques for On-Device Vision-based Crack Detection
Yuxuan Zhang, Luciano Sebastian Martinez-Rau, Quynh Nguyen Phuong Vu +2
Structural Health Monitoring (SHM) ensures the safety and longevity of infrastructure by enabling timely damage detection. Vision-based crack detection, combined with UAVs, address…
Comparison of Tiny Machine Learning Techniques for Embedded Acoustic Emission Analysis
Uditha Muthumala, Yuxuan Zhang, Luciano Sebastian Martinez-Rau +1
This paper compares machine learning approaches with different input data formats for the classification of acoustic emission (AE) signals. AE signals are a promising monitoring te…
On-device Anomaly Detection in Conveyor Belt Operations
Luciano S. Martinez-Rau, Yuxuan Zhang, Bengt Oelmann +1
Conveyor belts are crucial in mining operations by enabling the continuous and efficient movement of bulk materials over long distances, which directly impacts productivity. While…
An artificial neural network-based system for detecting machine failures using tiny sound data: A case study
Thanh Tran, Sebastian Bader, Jan Lundgren
In an effort to advocate the research for a deep learning-based machine failure detection system, we present a case study of our proposed system based on a tiny sound dataset. Our…
Denoising Induction Motor Sounds Using an Autoencoder
Thanh Tran, Sebastian Bader, Jan Lundgren
Denoising is the process of removing noise from sound signals while improving the quality and adequacy of the sound signals. Denoising sound has many applications in speech process…