Related papers: CWT-Enhanced Vibration Sensing With Spatial Fault …
Ultra-wideband (UWB) based positioning with fewer anchors has attracted significant research interest in recent years, especially under energy-constrained conditions. However, most existing methods rely on discrete-time representations and…
Low-light conditions and occluded scenarios impede object detection in real-world Internet of Things (IoT) applications like autonomous vehicles and security systems. While advanced machine learning models strive for accuracy, their…
Time series data and their time-frequency representation from gravitational-wave interferometers present multiple opportunities for the use of artificial intelligence methods associated with signal and image processing. Closely connected…
Shortwave track diseases are generally reflected in the form of local track irregularity. Such diseases will greatly impact the train-track-bridge interaction (TTBI) dynamic system, seriously affecting train safety. Therefore, a method is…
Purpose: This paper aims to enhance bearing fault diagnosis in industrial machinery by introducing a novel method that combines Graph Attention Network (GAT) and Long Short-Term Memory (LSTM) networks. This approach captures both spatial…
This paper improves visual-inertial systems to boost the localization accuracy for low-cost rescue robots. When robots traverse on rugged terrain, the performance of pose estimation suffers from big noise on the measurements of the inertial…
End-to-end production of object tracklets from high resolution video in real-time and with high accuracy remains a challenging problem due to the cost of object detection on each frame. In this work we present Localization-based Tracking…
The integrity of offshore wind turbines, pivotal for sustainable energy generation, is often compromised by surface material defects. Despite the availability of various detection techniques, limitations persist regarding…
Wide Area Measurement Systems (WAMS) can guide system operators' to increase their situational awareness by expanding observability of their supervise area and adjoining systems. Power system oscillations in the electrical grid are a matter…
Wavelets are waveform functions that describe transient and unstable variations, such as noises. In this work, we study the advantages of discrete and continuous wavelet transforms (DWT and CWT) of microlensing data to denoise them and…
Visual-inertial odometry (VIO) is widely used for mobile robot localization, but its long-term accuracy degrades without global constraints. Incorporating ranging sensors such as ultra-wideband (UWB) can mitigate drift; however,…
Object localization in satellite imagery is particularly challenging due to the high variability of objects, low spatial resolution, and interference from noise and dominant features such as clouds and city lights. In this research, we…
World foundation models, which simulate the physical world by predicting future states from current observations and inputs, have become central to many applications in physical intelligence, including autonomous driving and robotics.…
Diagnosis of bearing faults is paramount to reducing maintenance costs and operational breakdowns. Bearing faults are primary contributors to machine vibrations, and analyzing their signal morphology offers insights into their health…
Vibrations of damaged bearings are manifested as modulations in the amplitude of the generated vibration signal, making envelope analysis an effective approach for discriminating between healthy and abnormal vibration patterns. Motivated by…
In this paper, we propose a method to improve the accuracy of speech emotion recognition (SER) by using vision transformer (ViT) to attend to the correlation of frequency (y-axis) with time (x-axis) in spectrogram and transferring…
We aim at providing the object detection community with an efficient and performant object detector, termed YOLO-MS. The core design is based on a series of investigations on how multi-branch features of the basic block and convolutions…
In increasing number of electronic devices implement wideband radio technologies for localization and sensing purposes, like ultra-wideband (UWB). Such radio technologies benefit from a large number of antennas, but space for antennas is…
Traditional fault diagnosis methods using Convolutional Neural Networks (CNNs) often struggle with capturing the temporal dynamics of vibration signals. To overcome this, the application of Transformer-based Vision Transformer (ViT) methods…
To address the issues of slow detection speed,low accuracy,difficulty in deployment on industrial edge devices,and large parameter and computational requirements in deep learning-based coal gangue target detection methods,we propose a…