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 …
Research review for broad learning system: Algorithms, theory, and applications
In recent years, the appearance of the broad learning system (BLS) is poised to
revolutionize conventional artificial intelligence methods. It represents a step toward building …
revolutionize conventional artificial intelligence methods. It represents a step toward building …
Unsupervised K-means clustering algorithm
KP Sinaga, MS Yang - IEEE access, 2020 - ieeexplore.ieee.org
The k-means algorithm is generally the most known and used clustering method. There are
various extensions of k-means to be proposed in the literature. Although it is an …
various extensions of k-means to be proposed in the literature. Although it is an …
A review of unsupervised feature selection methods
S Solorio-Fernández, JA Carrasco-Ochoa… - Artificial Intelligence …, 2020 - Springer
In recent years, unsupervised feature selection methods have raised considerable interest in
many research areas; this is mainly due to their ability to identify and select relevant features …
many research areas; this is mainly due to their ability to identify and select relevant features …
Advances in computational intelligence of polymer composite materials: machine learning assisted modeling, analysis and design
The superior multi-functional properties of polymer composites have made them an ideal
choice for aerospace, automobile, marine, civil, and many other technologically demanding …
choice for aerospace, automobile, marine, civil, and many other technologically demanding …
Learning models with uniform performance via distributionally robust optimization
JC Duchi, H Namkoong - The Annals of Statistics, 2021 - projecteuclid.org
Learning models with uniform performance via distributionally robust optimization Page 1 The
Annals of Statistics 2021, Vol. 49, No. 3, 1378–1406 https://doi.org/10.1214/20-AOS2004 © …
Annals of Statistics 2021, Vol. 49, No. 3, 1378–1406 https://doi.org/10.1214/20-AOS2004 © …
[图书][B] Model-based clustering and classification for data science: with applications in R
Cluster analysis finds groups in data automatically. Most methods have been heuristic and
leave open such central questions as: how many clusters are there? Which method should I …
leave open such central questions as: how many clusters are there? Which method should I …
A fuzzy C-means algorithm for optimizing data clustering
SE Hashemi, F Gholian-Jouybari… - Expert Systems with …, 2023 - Elsevier
Big data has increasingly become predominant in many research fields affecting human
knowledge, including medicine and engineering. Cluster analysis, or clustering, is widely …
knowledge, including medicine and engineering. Cluster analysis, or clustering, is widely …
Unsupervised machine learning for networking: Techniques, applications and research challenges
While machine learning and artificial intelligence have long been applied in networking
research, the bulk of such works has focused on supervised learning. Recently, there has …
research, the bulk of such works has focused on supervised learning. Recently, there has …
[HTML][HTML] Optical sensors and machine learning algorithms in sensor-based material flow characterization for mechanical recycling processes: A systematic literature …
Digital technologies hold enormous potential for improving the performance of future-
generation sorting and processing plants; however, this potential remains largely untapped …
generation sorting and processing plants; however, this potential remains largely untapped …