The Industry Classification Benchmark (ICB) is a globally recognized system that categorizes stocks into industries, ...

Abstract: Convolutional neural networks (CNNs) are widely adopted for remote sensing image scene classification. However, labeling of large annotated remote sensing datasets is costly and time ...

North America held a dominan Market position, capturing more than a 38.9% share, holding USD 6.6 Billion revenue.

Background/Aims On 17 September 2024, over 3000 pager devices containing explosives were remotely detonated across Lebanon in a coordinated mass-casualty event, causing unprecedented ocular trauma.

Introduction: Classification systems aim to minimise the impact of impairment on competition outcome. To measure the effectiveness of a classification system, the relationship between impairment and ...

Learning representations on the Grassmannian manifold is popular in quite a few visual classification tasks. With the development of deep learning techniques, several neural networks have recently ...

The goal of a machine learning binary classification problem is to predict a variable that has exactly two possible values. For example, you might want to predict the sex of a company employee (male = ...

OBJECTIVE: Obesity is a global health problem. The aim is to analyze the effectiveness of machine learning models in predicting obesity classes and to determine which model performs best in obesity ...

Bangladesh is set to incorporate data classification into its Personal Data Protection Act, said Chief Adviser's Special Assistant Faiz Ahmad Taiyeb. Data components used to identify individuals will ...

As organizations evolve, traditional data classification—typically designed for regulatory, finance or customer data—is being stretched to accommodate employee data. While classification processes and ...