CANNIBAL Unveils the Hidden Gems: Hyperspectral Band Selection via Clustering of Weighted Variable Interaction Graphs
Author:
Affiliation:
1. Silesian University of Technology, Gliwice, Poland
2. Wroclaw University of Science and Technology, Wroclaw, Poland
3. University of São Paulo, Ribeirao Preto, Sao Paulo, Brazil
Funder
Narodowe Centrum Nauki
Publisher
ACM
Reference45 articles.
1. Deep Learning in Hyperspectral Unmixing: A Review
2. Expanding from Discrete Cartesian to Permutation Gene-pool Optimal Mixing Evolutionary Algorithms
3. W. Chen T. Weise Z. Yang and K. Tang. 2010. Large-Scale Global Optimization Using Cooperative Coevolution with Variable Interaction Learning. In Parallel Problem Solving from Nature PPSN XI Robert Schaefer Carlos Cotta Joanna Kołodziej and Günter Rudolph (Eds.). Springer Berlin Heidelberg Berlin Heidelberg 300--309.
4. Hyperspectral imaging in forensic science: An overview of major application areas
5. A comprehensive survey of clustering algorithms: State-of-the-art machine learning applications, taxonomy, challenges, and future research prospects
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