Hyperspectral Image Classification On Kennedy

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OA@15perclass

Ergebnisse

Leistungsergebnisse verschiedener Modelle zu diesem Benchmark

		Paper Title
RPNet-RF	98.51	Small Sample Hyperspectral Image Classification Based on the Random Patches Network and Recursive Filtering
TC-GAN	98.39±0.63	Generative Adversarial Networks Based on Transformer Encoder and Convolution Block for Hyperspectral Image Classification
DCFSL	97.59±1.03	Graph Information Aggregation Cross-Domain Few-Shot Learning for Hyperspectral Image Classification
RPNet	95.83	Hyperspectral image classification via a random patches network
S-DMM	95.83±1.68	Deep Metric Learning-Based Feature Embedding for Hyperspectral Image Classification
IFRF	95.07	Feature Extraction of Hyperspectral Images With Image Fusion and Recursive Filtering
CA-GAN	91.17±1.54	Generative Adversarial Networks Based on Collaborative Learning and Attention Mechanism for Hyperspectral Image Classification
3D-CNN	87.18±1.00	Spectral–Spatial Classification of Hyperspectral Imagery with 3D Convolutional Neural Network
HSI-BERT	82.93±0.94	HSI-BERT: Hyperspectral Image Classification Using the Bidirectional Encoder Representation From Transformers
2D-CNN	80.53±1.31	Deep supervised learning for hyperspectral data classification through convolutional neural networks
3D VS-CNN	80.15±0.62	Hyperspectral Image Classification of Convolutional Neural Network Combined with Valuable Samples
SSBC	-	Discrete Cosine Transform-Based Joint Spectral-Spatial Information Compression and Band Correlation Calculation for Hyperspectral Feature Extraction
CVSSN	-	Exploring the Relationship between Center and Neighborhoods: Central Vector oriented Self-Similarity Network for Hyperspectral Image Classification
A2S2K-ResNet	-	Attention-Based Adaptive Spectral-Spatial Kernel ResNet for Hyperspectral Image Classification

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Hyperspectral Image Classification On Kennedy | SOTA | HyperAI