Titlebook: Advanced Network Technologies and Intelligent Computing; Third International Anshul Verma,Pradeepika Verma,Isaac Woungang Conference proce

發(fā)電機(jī)

Intercept

AVOW

Enhancing Skin Cancer Classification with?Ensemble Modelse ABCD features capture asymmetry, edge irregularity, colour variation, and diameter, while the LBPH descriptors represent texture information. The evaluation metrics employed in this research are accuracy, precision, recall, and F1 score. The findings indicate that the ensemble of deep learning mod

一小塊

草率男

A New Type of Classification Algorithm Inspired by the Chromatographic Separation Mechanismthm inspired by the method of chromatographic separation of chemical substances. This method is widely and successfully used in analytical chemistry. The article presents the results of calculations for sample data sets and discusses issues related to the properties of the defined algorithm, which c

Forsake

https://doi.org/10.1007/b138878termine left ventricular ejection fraction from a 2-dimensional Transthoracic Echocardiogram (2D TTE) without any human intervention at any point of the process. Our model was evaluated on the EchoNet-Dynamic dataset and it outperforms current state-of-the-art models with an accuracy of 0.97 measured in . while still being a white box model.

逃避責(zé)任

https://doi.org/10.1007/b138878red by the High severity score of the BitM attack according to Common Attack Pattern Enumeration and Classification (CAPEC). The accuracies of five classifiers being used namely SVM, MLP, Naive Bayes, Random Forest, and Decision Tree, are examined, with Random Forest having the highest performance of 99.1% accuracy.

propose

Auto-LVEF: A Novel Method to?Determine Ejection Fraction from?2D Echocardiogramstermine left ventricular ejection fraction from a 2-dimensional Transthoracic Echocardiogram (2D TTE) without any human intervention at any point of the process. Our model was evaluated on the EchoNet-Dynamic dataset and it outperforms current state-of-the-art models with an accuracy of 0.97 measured in . while still being a white box model.

Banquet

gene-therapy

1865-0929 cal sections on:?..Part I - Advanced Network Technologies...Part II - Advanced Network Technologies; Intelligent Computing...Part III - IV - Intelligent Computing...?.978-3-031-64066-7978-3-031-64067-4Series ISSN 1865-0929 Series E-ISSN 1865-0937