Mean shift-based clustering of remotely sensed data with agricultural and land-cover applications-Reference-Cited by-同舟云学术

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Mean shift-based clustering of remotely sensed data with agricultural and land-cover applications

Published:2013-05-23 Issue:17 Volume:34 Page:6037-6053
ISSN:0143-1161
Container-title:International Journal of Remote Sensing
language:en
Short-container-title:International Journal of Remote Sensing

Author:

Friedman Lior¹,Netanyahu Nathan S.¹²,Shoshany Maxim³

Affiliation:

1. a Department of Computer Science , Bar-Ilan University , Ramat-Gan , 52900 , Israel

2. b Center for Automation Research, University of Maryland , College Park , MD , 20742 , USA

3. c Department of Civil and Environmental Engineering , Technion, Israel Institute of Technology , Haifa , 32000 , Israel

Publisher

Informa UK Limited

Subject

General Earth and Planetary Sciences

Link

https://www.tandfonline.com/doi/pdf/10.1080/01431161.2013.793866

Reference35 articles.

1. Statistical pattern recognition: a review

2. Satellite image classification using genetically guided fuzzy clustering with spatial information

3. Mean-shift and hierarchical clustering for textured polarimetric SAR image segmentation/classification

4. Mean shift‐based clustering analysis of multispectral remote sensing imagery

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1. Object detection and tracking in Precision Farming: a systematic review;Computers and Electronics in Agriculture;2024-04

2. Active Pairwise Constraint Learning in Constrained Time-Series Clustering for Crop Mapping from Airborne SAR Imagery;Remote Sensing;2022-11-30

3. Automatic detection of single street trees from airborne LiDAR data based on point segmentation methods;International Journal of Engineering and Geosciences;2022-08-09

4. On the convergence and consistency of the blurring mean-shift process;Annals of the Institute of Statistical Mathematics;2014-01-03

5. Remote Sensing for sustainable agriculture;International Journal of Remote Sensing;2013-06-14

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