A Novel Method for Multispectral Image Classification by Using Social Spider Optimization Algorithm Integrated to Fuzzy C-Mean Clustering
Published 2019 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
A Novel Method for Multispectral Image Classification by Using Social Spider Optimization Algorithm Integrated to Fuzzy C-Mean Clustering
Authors
Keywords
-
Journal
CANADIAN JOURNAL OF REMOTE SENSING
Volume -, Issue -, Pages 1-12
Publisher
Informa UK Limited
Online
2019-05-16
DOI
10.1080/07038992.2019.1610369
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- Whale Optimization Algorithm and Adaptive Neuro-Fuzzy Inference System: a hybrid method for feature selection and land pattern classification
- (2019) Quang-Thanh Bui et al. INTERNATIONAL JOURNAL OF REMOTE SENSING
- Hyperspectral Image Classification for Land Cover Based on an Improved Interval Type-II Fuzzy C-Means Approach
- (2018) Hongyuan Huo et al. SENSORS
- Hybrid model to optimize object-based land cover classification by meta-heuristic algorithm: an example for supporting urban management in Ha Noi, Viet Nam
- (2018) Quang-Thanh Bui et al. International Journal of Digital Earth
- Adaptive Scale Selection for Multiscale Segmentation of Satellite Images
- (2017) Yanan Zhou et al. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
- A review of supervised object-based land-cover image classification
- (2017) Lei Ma et al. ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING
- Object-based water body extraction model using Sentinel-2 satellite imagery
- (2017) Gordana Kaplan et al. European Journal of Remote Sensing
- Adaptive Mean Shift-Based Identification of Individual Trees Using Airborne LiDAR Data
- (2017) Xingbo Hu et al. Remote Sensing
- Remote sensing clustering analysis based on object-based interval modeling
- (2016) Hui He et al. COMPUTERS & GEOSCIENCES
- A Novel Approach for Multispectral Satellite Image Classification Based on the Bat Algorithm
- (2016) J. Senthilnath et al. IEEE Geoscience and Remote Sensing Letters
- A social spider algorithm for global optimization
- (2015) James J.Q. Yu et al. APPLIED SOFT COMPUTING
- Benchmarking of Remote Sensing Segmentation Methods
- (2015) Stanislav Mikes et al. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
- Comparing Machine Learning Classifiers for Object-Based Land Cover Classification Using Very High Resolution Imagery
- (2014) Yuguo Qian et al. Remote Sensing
- A Novel Clustering-Based Feature Representation for the Classification of Hyperspectral Imagery
- (2014) Qikai Lu et al. Remote Sensing
- Performance Evaluation of Machine Learning Algorithms for Urban Pattern Recognition from Multi-spectral Satellite Images
- (2014) Marc Wieland et al. Remote Sensing
- Unsupervised classification based on fuzzyc-means with uncertainty analysis
- (2013) Qunming Wang et al. Remote Sensing Letters
- Remote Sensing Classification Using Fuzzy C-means Clustering with Spatial Constraints Based on Markov Random Field
- (2013) Yang HongLei et al. European Journal of Remote Sensing
- Image segmentation scale parameter optimization and land cover classification using the Random Forest algorithm
- (2011) A. Smith Journal of Spatial Science
- A comparison of pixel-based and object-based image analysis with selected machine learning algorithms for the classification of agricultural landscapes using SPOT-5 HRG imagery
- (2011) Dennis C. Duro et al. REMOTE SENSING OF ENVIRONMENT
- Clustering using firefly algorithm: Performance study
- (2011) J. Senthilnath et al. Swarm and Evolutionary Computation
- Support vector machines in remote sensing: A review
- (2010) Giorgos Mountrakis et al. ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING
- Mean shift‐based clustering analysis of multispectral remote sensing imagery
- (2009) S. Bo et al. INTERNATIONAL JOURNAL OF REMOTE SENSING
Discover Peeref hubs
Discuss science. Find collaborators. Network.
Join a conversationAsk a Question. Answer a Question.
Quickly pose questions to the entire community. Debate answers and get clarity on the most important issues facing researchers.
Get Started