Latest research trends in fall detection and prevention using machine learning: A systematic review
Falls are unusual actions that cause a significant health risk among older people. The
growing percentage of people of old age requires urgent development of fall detection and …
growing percentage of people of old age requires urgent development of fall detection and …
[HTML][HTML] Intelligent prediction of slope stability based on visual exploratory data analysis of 77 in situ cases
G Wang, B Zhao, B Wu, C Zhang, W Liu - International Journal of Mining …, 2023 - Elsevier
Slope stability prediction research is a complex non-linear system problem. In carrying out
slope stability prediction work, it often encounters low accuracy of prediction models and …
slope stability prediction work, it often encounters low accuracy of prediction models and …
The role of intelligent technologies in early detection of autism spectrum disorder (asd): A scoping review
M Kohli, AK Kar, S Sinha - IEEE Access, 2022 - ieeexplore.ieee.org
Background: Two-year delay is reported between the first developmental concern raised by
the parents and the diagnosis of ASD (Autism Spectrum Disorder), delaying the start of early …
the parents and the diagnosis of ASD (Autism Spectrum Disorder), delaying the start of early …
Healthcare professional in the loop (HPIL): classification of standard and oral cancer-causing anomalous regions of oral cavity using textural analysis technique in …
Oral mucosal lesions (OML) and oral potentially malignant disorders (OPMDs) have been
identified as having the potential to transform into oral squamous cell carcinoma (OSCC) …
identified as having the potential to transform into oral squamous cell carcinoma (OSCC) …
On the precise error analysis of support vector machines
A Kammoun, MS AlouiniFellow - IEEE Open Journal of Signal …, 2021 - ieeexplore.ieee.org
This paper investigates the asymptotic behavior of the soft-margin and hard-margin support
vector machine (SVM) classifiers for simultaneously high-dimensional and numerous data …
vector machine (SVM) classifiers for simultaneously high-dimensional and numerous data …
Discriminative subspace learning via optimization on Riemannian manifold
W Yin, Z Ma, Q Liu - Pattern Recognition, 2023 - Elsevier
Discriminative subspace learning is an important problem in machine learning, which aims
to find the maximum separable decision subspace. Traditional Euclidean-based methods …
to find the maximum separable decision subspace. Traditional Euclidean-based methods …
Toward smart manufacturing: Analysis and classification of cutting parameters and energy consumption patterns in turning processes
Advanced monitoring technologies with embedded devices, sensors, and wireless data
communication have been developed to capture machine, process, tool dconditions, and …
communication have been developed to capture machine, process, tool dconditions, and …
Optimal linear discriminant analysis for high-dimensional functional data
Most of existing methods of functional data classification deal with one or a few processes. In
this work we tackle classification of high-dimensional functional data, in which each …
this work we tackle classification of high-dimensional functional data, in which each …
Reformative ROCOSD–ORESTE–LDA model with an MLP neural network to enhance decision reliability
X Wang, B Hou, Y Teng, Y Yang, X Zhang, L Sun… - Knowledge-Based …, 2024 - Elsevier
Multi-criteria decision-making (MCDM) problems require a decision model and outcomes
that are stable and reliable, which is especially true for safety systems. To this end, we …
that are stable and reliable, which is especially true for safety systems. To this end, we …