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Hyperspectral Image Classification On Pavia

Metrics

AA@5%perclass
Kappa@5%perclass
OA@5%perclass
Overall Accuracy

Results

Performance results of various models on this benchmark

Paper TitleRepository
JigsawHSI---100.00JigsawHSI: a network for Hyperspectral Image classification
SpectralNET---99.99%SpectralNET: Exploring Spatial-Spectral WaveletCNN for Hyperspectral Image Classification
Deep Matrix Capsules---99.99%Hyperspectral Image Classification Using Deep Matrix Capsules-
SSDGL---99.97%A Spectral-Spatial-Dependent Global Learning Framework for Insufficient and Imbalanced Hyperspectral Image Classification
FSKNet---99.96%Faster hyperspectral image classification based on selective kernel mechanism using deep convolutional networks
A2S2K-ResNet---99.85Attention-Based Adaptive Spectral-Spatial Kernel ResNet for Hyperspectral Image Classification-
FPGA---99.81%FPGA: Fast Patch-Free Global Learning Framework for Fully End-to-End Hyperspectral Image Classification
CVSSN99.52±0.17%0.9957±0.000999.68±0.06%99.68±0.06%Exploring the Relationship between Center and Neighborhoods: Central Vector oriented Self-Similarity Network for Hyperspectral Image Classification-
A-SPN---99.65%Attention-Based Second-Order Pooling Network for Hyperspectral Image Classification-
WCRN---99.43%Wide Contextual Residual Network with Active Learning for Remote Sensing Image Classification-
St-SS-pGRU---98.44%Shorten Spatial-spectral RNN with Parallel-GRU for Hyperspectral Image Classification
AMS-M2ESL---98.09±0.30%Adaptive Mask Sampling and Manifold to Euclidean Subspace Learning with Distance Covariance Representation for Hyperspectral Image Classification-
BASSNet---97.48%BASS Net: Band-Adaptive Spectral-Spatial Feature Learning Neural Network for Hyperspectral Image Classification
DeepHyperX 3D CNN---96.71Deep Learning for Classification of Hyperspectral Data: A Comparative Review
CNN-MRF---96.18Hyperspectral Image Classification with Markov Random Fields and a Convolutional Neural Network
3D VS-CNN----Hyperspectral Image Classification of Convolutional Neural Network Combined with Valuable Samples-
HSI-BERT----HSI-BERT: Hyperspectral Image Classification Using the Bidirectional Encoder Representation From Transformers-
S-DMM----Deep Metric Learning-Based Feature Embedding for Hyperspectral Image Classification-
IFRF----Feature Extraction of Hyperspectral Images With Image Fusion and Recursive Filtering-
HyLITE----Locality-Aware Hyperspectral Classification
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Hyperspectral Image Classification On Pavia | SOTA | HyperAI