K-means clustering algorithms: A comprehensive review, variants analysis, and advances in the era of big data
Advances in recent techniques for scientific data collection in the era of big data allow for the
systematic accumulation of large quantities of data at various data-capturing sites. Similarly …
systematic accumulation of large quantities of data at various data-capturing sites. Similarly …
[HTML][HTML] Financial fraud: a review of anomaly detection techniques and recent advances
With the rise of technology and the continued economic growth evident in modern society,
acts of fraud have become much more prevalent in the financial industry, costing institutions …
acts of fraud have become much more prevalent in the financial industry, costing institutions …
[HTML][HTML] Deep learning in food category recognition
Integrating artificial intelligence with food category recognition has been a field of interest for
research for the past few decades. It is potentially one of the next steps in revolutionizing …
research for the past few decades. It is potentially one of the next steps in revolutionizing …
AI-based evaluation system for supply chain vulnerabilities and resilience amidst external shocks: An empirical approach
The study focuses on the intricacies and vulnerabilities inherent in supply chains, which are
often influenced by external disruptions such as pandemics, conflict scenarios, and inflation …
often influenced by external disruptions such as pandemics, conflict scenarios, and inflation …
[HTML][HTML] Predictive maintenance enabled by machine learning: Use cases and challenges in the automotive industry
A Theissler, J Pérez-Velázquez, M Kettelgerdes… - Reliability engineering & …, 2021 - Elsevier
Recent developments in maintenance modelling fueled by data-based approaches such as
machine learning (ML), have enabled a broad range of applications. In the automotive …
machine learning (ML), have enabled a broad range of applications. In the automotive …
Challenges in predictive maintenance–A review
Predictive maintenance (PdM) aims the reduction of costs to increase the competitive
strength of the enterprises. It uses sensor data together with analytics techniques to optimize …
strength of the enterprises. It uses sensor data together with analytics techniques to optimize …
Self-supervised learning methods and applications in medical imaging analysis: A survey
The scarcity of high-quality annotated medical imaging datasets is a major problem that
collides with machine learning applications in the field of medical imaging analysis and …
collides with machine learning applications in the field of medical imaging analysis and …
Annual Research Review: The transdiagnostic revolution in neurodevelopmental disorders
Practitioners frequently use diagnostic criteria to identify children with neurodevelopmental
disorders and to guide intervention decisions. These criteria also provide the organising …
disorders and to guide intervention decisions. These criteria also provide the organising …
A quantitative discriminant method of elbow point for the optimal number of clusters in clustering algorithm
C Shi, B Wei, S Wei, W Wang, H Liu, J Liu - EURASIP journal on wireless …, 2021 - Springer
Clustering, a traditional machine learning method, plays a significant role in data analysis.
Most clustering algorithms depend on a predetermined exact number of clusters, whereas …
Most clustering algorithms depend on a predetermined exact number of clusters, whereas …
A survey of machine and deep learning methods for internet of things (IoT) security
The Internet of Things (IoT) integrates billions of smart devices that can communicate with
one another with minimal human intervention. IoT is one of the fastest developing fields in …
one another with minimal human intervention. IoT is one of the fastest developing fields in …