ClusterMPP: An unsupervised density-based clustering algorithm via Marked Point Process-Reference-Cited by-同舟云学术

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ClusterMPP: An unsupervised density-based clustering algorithm via Marked Point Process

Published:2017-08-19 Issue:4 Volume:21 Page:827-847
ISSN:1088-467X
Container-title:Intelligent Data Analysis
language:
Short-container-title:IDA

Author:

Henni Khadidja¹,Alata Olivier²,Zaoui Lynda¹,Vannier Brigitte³,Idrissi Abdellatif El⁴,Moussa Ahmed⁵

Affiliation:

1. LSSD Laboratory, Department of Computer Science, University of science and Technology, Oran, Algeria, Algeria

2. Hubert Curien Laboratory, UMR CNRS 5516, Jean Monnet University, France

3. Receptors, Regulation and Tumor Cells Laboratory, Poitiers University, France

4. ENSA-Tangier, Abdelmalek Essaadi University, Tangier, Morocco

5. Systems and Data Engineering Team, ENSA-Tangier, Abdelmalek Essaadi University, Tangier, Morocco

Publisher

IOS Press

Subject

Artificial Intelligence,Computer Vision and Pattern Recognition,Theoretical Computer Science

Reference46 articles.

1. Big Data, Data Science and Analytics the Opportunity and Challenge for IS Research;Agarwal;Information Systems Research,2014

2. Grouping/degrouping point process, a point process driven by geometrical and topological properties of a partition in regions;Alata;Computer Vision and Image Understanding,2011

3. C. Benedek, Detection of soldering defects in Printed Circuit Boards with Hierarchical Marked Point Processes, Pattern Recognition Letters 32(13) (2011), 1535–1543.

4. Building Development Monitoring in Multitemporal Remotely Sensed Image Pairs with Stochastic Birth-Death Dynamics;Benedek;Pattern Analysis and Machine Intelligence, IEEE Transactions,2012

5. Automated Extraction of Building Outlines From Airborne Laser Scanning Point Clouds;Yang;Geoscience and Remote Sensing Letters, IEEE,2013

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Cluster Density Properties Define a Graph for Effective Pattern Feature Selection;IEEE Access;2020

2. Is-ClusterMPP: clustering algorithm through point processes and influence space towards high-dimensional data;Advances in Data Analysis and Classification;2019-11-27

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