yanxum / aco_feature_selection_svm_classifyLinks
Ant colony optimization (aco) algorithm is used to select the features of hyperspectral remote sensing image bands,And then use Support Vector Machines(svm) to classify pixels.
☆38Updated 6 years ago
Alternatives and similar repositories for aco_feature_selection_svm_classify
Users that are interested in aco_feature_selection_svm_classify are comparing it to the libraries listed below
Sorting:
- Spectral data processing, including preprocessing, feature extraction, sample division, modeling, optimization algorithm.☆90Updated 5 years ago
- [IEEE TCYB 2022] Region-aware Hierarchical Latent Feature Representation Learning Guided Clustering for Hyperspectral Band Selection.☆14Updated 2 years ago
- The code of paper "Spectral-Spatial Genetic Algorithm-Based Unsupervised Band Selection for Hyperspectral Image Classification"☆12Updated 4 years ago
- Hyperspectral CNN compression and band selection☆34Updated 5 years ago
- This is a code set for spectral-spatial hyperpsectral classifcation, including the EMAP, Gabor, LORSAL, LibSVM, MRF, and LBP methods.☆64Updated last year
- Band selection and classification of hyperspectral images using Multi-objective Genetic Algorithms☆14Updated 7 years ago
- Hyperspectral Band Selection using Self-Representation Learning with Sparse 1D-Operational Autoencoder (SRL-SOA)☆24Updated 10 months ago
- ☆44Updated 7 years ago
- ☆46Updated 5 years ago
- This is the code of "Hyperspectral Image Classification with Convolutional Neural Network and Active Learning".☆42Updated 6 years ago
- ☆56Updated 3 years ago
- The code of the paper "Flexible Gabor-based Superpixel-level Unsupervised LDA for Hyperspectral Image Classification".☆14Updated 5 years ago
- Hyperspectral image classification by exploring deep tensor facorization, published in IGARSS 2018.☆16Updated 7 years ago
- Unsupervised Spatial-Spectral Feature Learning by 3-Dimensional Convolutional Autoencoder for Hyperspectral Classification☆94Updated 4 years ago
- Independent component analysis for dimensionality reduction of hyperspectral images☆14Updated 6 years ago
- This is a demo program for Box-plot figure or statistical separability analysis figure, which can be used for hyperspectral target detect…☆15Updated 4 years ago
- In the hyperspectral unmixing literature, endmember extraction is addressed majorly using three methods i.e. Statistical, Sparse-regressi…☆11Updated 5 years ago
- Collaborative representation with background purification and saliency weight for hyperspectral anomaly detection☆21Updated 4 years ago
- BS-Nets: An End-to-End Framework for Band Selection of Hyperspectral Image☆41Updated 6 years ago
- The tensorflow code of the paper"Dual-Graph Convolutional Network Based on Band Attention and Sparse Constraint for Hyperspectral Band Se…☆15Updated 4 years ago
- This is a code set for hyperpsectral anomaly detection including the RX, PTA, CRD, iForest, SSIIFD, MFIFD etc.☆26Updated 2 years ago
- Hyperspectral image Target Detection based on Sparse Representation☆77Updated 7 years ago
- A pytorch implementation of paper "Transferred Deep Learning for Anomaly Detection in Hyperspectral Imagery"☆51Updated 6 years ago
- ☆29Updated 4 years ago
- A superpixel-based relational auto-encoder for feature extraction of hyperspectral images☆13Updated 6 years ago
- A PyTorch implementation of CNN+Vision Transformer for hyperspectral image classification☆80Updated 4 years ago
- Classification of Hyperspectral Remote Sensing Images Based on Convolutional Neural Network☆21Updated 6 years ago
- Hyperspectral Remote Sensing Scenes☆59Updated 4 years ago
- Developing Low-Cost Multispectral Imagers using Inter-Band Redundancy Analysis and Greedy Spectral Selection in Hyperspectral Imaging. Re…☆63Updated last year
- This Toolbox includes Hyperspectral Feature Extraction Techniques including Unsupervised, Supervised, and Deep Feature Extraction☆135Updated 4 years ago