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Found 8 papers, 3 papers with code
Effective Transfer of Pretrained Large Visual Model for Fabric Defect Segmentation via Specifc Knowledge Injection
Fabric defect segmentation is integral to textile quality control.
Physically-Constrained Transfer Learning through Shared Abundance Space for Hyperspectral Image Classification
Transfer learning-based methods address this problem by pre-training in the source domain and fine-tuning on the target domain.
General Classification
Hyperspectral Image Classification
+1
Representative-Discriminative Learning for Open-set Land Cover Classification of Satellite Imagery
Although inherently a classification problem, both representative and discriminative aspects of data need to be exploited in order to better distinguish unknown classes from known.
Unsupervised Pansharpening Based on Self-Attention Mechanism
First, the self-attention mechanism is proposed where the spatial varying detail extraction and injection functions are estimated according to the attention representations indicating spectral characteristics of the MSI with sub-pixel accuracy.
Non-Local Representation based Mutual Affine-Transfer Network for Photorealistic Stylization
Photorealistic stylization aims to transfer the style of a reference photo onto a content photo in a natural fashion, such that the stylized image looks like a real photo taken by a camera.
Unsupervised and Unregistered Hyperspectral Image Super-Resolution with Mutual Dirichlet-Net
With this design, the network allows to extract correlated spectral and spatial information from unregistered images that better preserves the spectral information.
Unsupervised Trajectory Segmentation and Promoting of Multi-Modal Surgical Demonstrations
To improve the efficiency of surgical trajectory segmentation for robot learning in robot-assisted minimally invasive surgery, this paper presents a fast unsupervised method using video and kinematic data, followed by a promoting procedure to address the over-segmentation issue.
Unsupervised Sparse Dirichlet-Net for Hyperspectral Image Super-Resolution
We refer to the proposed architecture as unsupervised Sparse Dirichlet-Net, or uSDN.
