[HTML][HTML] A deep learning-based hyperspectral object classification approach via imbalanced training samples handling

MT Islam, MR Islam, MP Uddin, A Ulhaq - Remote Sensing, 2023 - mdpi.com
Object classification in hyperspectral images involves accurately categorizing objects based
on their spectral characteristics. However, the high dimensionality of hyperspectral data and …

[HTML][HTML] Detecting anomalies in blockchain transactions using machine learning classifiers and explainability analysis

M Hasan, MS Rahman, H Janicke, IH Sarker - Blockchain: Research and …, 2024 - Elsevier
As the use of Blockchain for digital payments continues to rise in popularity, it also becomes
susceptible to various malicious attacks. Successfully detecting anomalies within Blockchain …

[HTML][HTML] Consumer Default Risk Portrait: An Intelligent Management Framework of Online Consumer Credit Default Risk

M Zhu, BC Shia, M Su, J Liu - Mathematics, 2024 - mdpi.com
Online consumer credit services play a vital role in the contemporary consumer market. To
foster their sustainable development, it is essential to establish and strengthen the relevant …

Exploring Resampling Techniques in Credit Card Default Prediction

M Lokanan - 2024 - researchsquare.com
In the field of machine learning, the preparation of data is a pivotal step in optimizing model
performance. This paper delves into the crucial role of data cleaning and transformation …

Anomaly Detection in Blockchain Transactions using Machine Learning with Explainability Analysis

M Hasan - 2024 - 103.109.52.4
In the era of growing cryptocurrency adoption, Blockchain has emerged as a leading player
in the digital payment landscape. However, this widespread popularity also brings forth an …