A review of clustering techniques and developments

By Amit Kumar Saxena, Mukesh Prasad, Akshansh Gupta, Neha Bharill, Om Prakash Patel, Aruna Tiwari, Meng Joo Er, Weiping Ding, Chin-Teng Lin. Neurocomputing, 2017

1,203 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Computer Vision and Pattern Recognition

View Paper: https://www.semanticscholar.org/paper/aca1c582504edb2759ae946b1af8580e951f842e

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Joseph Homer Saleh
2. Zhaoyi Xu

In Computer Vision and Pattern Recognition

1. Joseph Homer Saleh
2. Zhaoyi Xu

Citations in the corpus

• Machine Learning for Reliability Engineering and Safety Applications: Review of Current Status and Future Opportunities (2020, methodology): “rom, and it can be overwhelming for the user to navigate the thicket of methods available for this task. Two excellent reviews of clustering methods can be found in Jain et al. [37] and Saxena et al. [38]. Clustering methods include the widely used K-means algorithm [39], a variety of hierarchical c”