Search Results - Computing methodologies / Machine learning / Machine learning algorithms
-
1
A fault diagnosis methodology for an external gear pump with the use of Machine Learning classification algorithms: Support Vector Machine and Multilayer Perceptron
Published 2020Get full text
Default Conference proceeding -
2
Adaptive frameworks for robust myoelectric hand gesture prediction using machine learning and deep learning
Published 2021“…The research conducted herein places a focus on supplying reliable operational performance and movement dexterity via myoelectric control using machine learning (ML) and deep learning (DL) strategies. …”
Get full text
Default Thesis -
3
-
4
Advancing healthcare AI: Methods to improve robustness, transparency and user-centric integration
Published 2025Get full text
Default Thesis -
5
Nonsmooth low-rank matrix recovery: methodology, theory and algorithm
Published 2021Get full text
Default Conference proceeding -
6
-
7
-
8
Using plantar pressure for free-living posture recognition and sedentary behaviour monitoring
Published 2018“…Afterwards, a novel methodology for measuring daily life sedentary behaviour using plantar pressure data and a machine learning predictive model is developed. …”
Get full text
Default Thesis -
9
Artificial intelligence and art history: looking at images in an algorithmic culture
Published 2026“…Contributors explore recent developments in machine learning and computer vision and debate whether algorithmic analyses of art open new possibilities for human seeing. …”
Get full text
Default Book -
10
Building accurate exchange-correlation functional for density functional theory through data analytics and optimization
Published 2025“…The recent advancements in data analytics techniques, such as machine learning, which excel in pattern recognition, offer new opportunities for more effective approximations of the XC functional. …”
Get full text
Default Article -
11
-
12
Application of response surface-corrected finite element model and Bayesian neural networks to predict the dynamic response of forth road bridges under strong winds
Published 2024“…This work proposes a dual-driven approach, integrating machine learning and FEM with GNSS and Earth Observation for Structural Health Monitoring (GeoSHM), to bridge the gap in the limited application of dual-driven methods primarily applied for small- and medium-sized bridges to large-span bridge structures. …”
Get full text
Default Article