Ship detention prediction via feature selection scheme and support vector machine (SVM)

S Wu, X Chen, C Shi, J Fu, Y Yan… - Maritime Policy & …, 2022 - Taylor & Francis
Ship detention decision plays a key role in port state control (PSC) inspection process,
which is compactly related to navigation safety and maritime environmental protection. Many …

MSFF-Net: multi-stream feature fusion network for surface electromyography gesture recognition

X Peng, X Zhou, H Zhu, Z Ke, C Pan - PLoS One, 2022 - journals.plos.org
In the field of surface electromyography (sEMG) gesture recognition, how to improve
recognition accuracy has been a research hotspot. The rapid development of deep learning …

[Retracted] News Text Classification Method and Simulation Based on the Hybrid Deep Learning Model

N Sun, C Du - Complexity, 2021 - Wiley Online Library
This paper uses the database as the data source, using bibliometrics and visual analysis
methods, to statistically analyze the relevant documents published in the field of text …

Retrospective Study of Convolutional Neural Network for Medical Image Analysis and a Deep Insight Through Histopathological Dataset

S Sharma, E Kumaraswamy, S Kumar - Computational Intelligence: Select …, 2023 - Springer
Convolutional neural network (CNN) has become a prominent technology of choice in
medical image analysis as CNN is easy to train and requires less pre-processing of data …

Invasive ductal carcinoma grade classification in histopathological images using transfer learning approach

E Kumaraswamy, S Sharma… - 2021 IEEE Bombay …, 2021 - ieeexplore.ieee.org
Cancer is the greatest cause of mortality in the world wherein; Breast Invasive Ductal
Carcinoma (IDC) is the second leading cause of death among women. Computer-assisted …

A novel approach to enhancing biomedical signal recognition via hybrid high-order information bottleneck driven spiking neural networks

K Wu, E Shunzhuo, N Yang, A Zhang, X Yan, C Mu… - Neural Networks, 2025 - Elsevier
Biomedical signals, encapsulating vital physiological information, are pivotal in elucidating
human traits and conditions, serving as a cornerstone for advancing human–machine …

Direct comparison of SVM and LR classifier for SEMG signal classification using TFD features

Y Narayan - Materials Today: Proceedings, 2021 - Elsevier
The performance of any bio-medical signal based robotic device depends upon the
classification accuracy of the system. In this context, surface electromyography (SEMG) …

A Machine Learning Model for Accurate Credit Risk Forecasting in Banking Systems: An Empirical Investigation

M Hasni, MS Aguir, MZ Babai… - International Journal of …, 2024 - search.proquest.com
Credit risk consists is the expectation of losses stemming from the inability of a borrower to
repay a loan. For the purpose of accurate control of credit risks, banking systems seek …

Analysis of MLP and DSLVQ classifiers for EEG signals based movements identification

Y Narayan - 2021 2nd Global Conference for Advancement in …, 2021 - ieeexplore.ieee.org
Brain-Computer Interfacing (BCI) is the latest research trend for develo** the rehabilitation
robotic system based on electroencephalogram (EEG) signals to make human life more …

DWT-based hand movement identification of EMG signals using SVM

V Ahlawat, Y Narayan, D Kumar - Proceedings of International Conference …, 2021 - Springer
Electromyogram (EMG) signals are widely used in rehabilitation, medical, engineering,
robotic, and industrial fields. For amputee's residual muscles control, EMG signals have …