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 …
Brain tumor segmentation of MRI images: A comprehensive review on the application of artificial intelligence tools
Background Brain cancer is a destructive and life-threatening disease that imposes
immense negative effects on patients' lives. Therefore, the detection of brain tumors at an …
immense negative effects on patients' lives. Therefore, the detection of brain tumors at an …
[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 …
Improved Gaussian mixture model to map the flooded crops of VV and VH polarization data
Accurate and timely monitoring of flooded crop areas is crucial for disaster rescue and loss
assessment. However, most flooded crop monitoring methods based on synthetic aperture …
assessment. However, most flooded crop monitoring methods based on synthetic aperture …
The k-means Algorithm: A Comprehensive Survey and Performance Evaluation
The k-means clustering algorithm is considered one of the most powerful and popular data
mining algorithms in the research community. However, despite its popularity, the algorithm …
mining algorithms in the research community. However, despite its popularity, the algorithm …
Modeling, diagnostics, optimization, and control of internal combustion engines via modern machine learning techniques: A review and future directions
A critical review of the existing Internal Combustion Engine (ICE) modeling, optimization,
diagnosis, and control challenges and the promising state-of-the-art Machine Learning (ML) …
diagnosis, and control challenges and the promising state-of-the-art Machine Learning (ML) …
Machine learning in additive manufacturing: State-of-the-art and perspectives
Additive manufacturing (AM) has emerged as a disruptive digital manufacturing technology.
However, its broad adoption in industry is still hindered by high entry barriers of design for …
However, its broad adoption in industry is still hindered by high entry barriers of design for …
Keyhole fluctuation and pore formation mechanisms during laser powder bed fusion additive manufacturing
Keyhole porosity is a key concern in laser powder-bed fusion (LPBF), potentially impacting
component fatigue life. However, some keyhole porosity formation mechanisms, eg, keyhole …
component fatigue life. However, some keyhole porosity formation mechanisms, eg, keyhole …
Expertise-structure and risk-appetite-integrated two-tiered collective opinion generation framework for large-scale group decision making
ZS Chen, X Zhang, RM Rodríguez… - … on Fuzzy Systems, 2022 - ieeexplore.ieee.org
The generation of collective preference assessments occupies a critical position in deriving
accurate and reliable alternative rankings in the context of large-scale group decision …
accurate and reliable alternative rankings in the context of large-scale group decision …
A survey of mmWave-based human sensing: Technology, platforms and applications
With the rapid development of the Internet of Things (IoT) and the rise of 5G communication
networks and automatic driving, millimeter wave (mmWave) sensing is emerging and starts …
networks and automatic driving, millimeter wave (mmWave) sensing is emerging and starts …