The learning process and hyper-parameter optimization of artificial neural networks (ANNs)
and deep learning (DL) architectures is considered one of the most challenging machine …

Abstract Convolutional Neural Network (CNN) is a prevalent topic in deep learning (DL)
research for their architectural advantages. CNN relies heavily on hyperparameter …

There are many kinds of Exploit Kits, each one being built with several vulnerabilities, but
almost all of them are written in JavaScript. So, we created an antivirus, endowed with …

Given the importance and interest of buildings in the urban environment, numerous studies
have focused on automatically extracting building outlines by exploiting different datasets …

Convolutional neural networks (CNNs) have exceptionally performed across various
computer vision tasks. However, their effectiveness depends heavily on the careful selection …

The aim of this work is to develop a classifier for the Indian classical dance (ICD) online
Bharatanatyam videos using deep learning techniques. Bharatanatyam is the most ancient …

'Ballet'is a-century concert performing dance form that originated in Italy. Current AI models
for ballet dance pose identification in live performance videos is challenging due to …

Human pose identification from 2D video sequences is extremely challenging under the
influence of recording artifacts such as lighting, sensor motion, unpredictable subject …

This paper presents a comprehensive survey of machine learning techniques used for
dance classification, especially in the context of dances of Indian origin. The advances and …

Density peak clustering (DPC) has shown promising results for many complex problems
when compared with other existing clustering techniques. Inspite of many advantages, DPC …