A Universal Knowledge Embedded Contrastive Learning Framework for Hyperspectral Image Classification

arXiv:2404.01673 · cs.CV · Submitted 2024-04-02 · Read on arXiv

cs.CV

Submitted: 2024-04-02

Updated: 2024-04-27

Code: https://github.com/quanweiliu/KnowCL

Terminology

• Semi-supervised Learning — 20× in this paper · explained in 4 episodes
• Loss Function — 17× in this paper · explained in 2 episodes
• Accuracy — 16× in this paper · explained in 1 episode
• Contrastive Learning — 16× in this paper · explained in 5 episodes
• Transformer — 12× in this paper · explained in 2 episodes
• Data Augmentation — 9× in this paper · explained in 7 episodes
• Feature Extraction — 9× in this paper · explained in 2 episodes
• Conference on Computer Vision and Pattern Recognition — 5× in this paper
• Generalization — 5× in this paper · explained in 13 episodes
• Benchmark — 4× in this paper · explained in 2 episodes
• Embeddings — 4× in this paper · explained in 2 episodes
• Fine-Tuning — 3× in this paper · explained in 5 episodes
• Pseudo-labels — 3× in this paper · explained in 2 episodes
• Attention Mechanism — 2× in this paper · explained in 2 episodes
• GNNs — 2× in this paper · explained in 2 episodes
• Regularization — 2× in this paper · explained in 3 episodes
• Representation Learning — 2× in this paper · explained in 2 episodes
• Ablation — 1× in this paper · explained in 1 episode
• Ablation study — 1× in this paper · explained in 1 episode
• Consistency — 1× in this paper · explained in 3 episodes
• Cosine Similarity — 1× in this paper · explained in 3 episodes
• Data Fusion — 1× in this paper · explained in 3 episodes
• Downstream Tasks — 1× in this paper · explained in 2 episodes
• Foundation Model — 1× in this paper · explained in 3 episodes
• Linear probe — 1× in this paper · explained in 2 episodes
• Predictive Coding — 1× in this paper · explained in 2 episodes
• Principal Component Analysis (PCA) — 1× in this paper · explained in 4 episodes
• Q-learning — 1× in this paper · explained in 3 episodes
• Self-Supervised Learning — 1× in this paper · explained in 7 episodes
• Vision Transformer (ViT) — 1× in this paper · explained in 2 episodes

Sources

• Unsupervised Feature Learning by Autoencoder and Prototypical Contrastive Learning for Hyperspectral Classification
• Representation Learning with Contrastive Predictive Coding
• Auxiliary Tasks in Multi-task Learning

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