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Found 4 papers, 1 papers with code
Contrastive-Based Deep Embeddings for Label Noise-Resilient Histopathology Image Classification
Recent advancements in deep learning have proven highly effective in medical image classification, notably within histopathology.
Classification in Histopathology: A unique deep embeddings extractor for multiple classification tasks
We demonstrate that thanks to this selection method, an optimal feature extractor can be selected for different tasks on the target domain.
Weakly Supervised Semantic Segmentation of Satellite Images
When one wants to train a neural network to perform semantic segmentation, creating pixel-level annotations for each of the images in the database is a tedious task.
Image search using multilingual texts: a cross-modal learning approach between image and text
Moreover, by using multilingual embeddings we ensure that words from two different languages have close descriptors and thus are attached to similar images.
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