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Found 6 papers, 3 papers with code
Stable Diffusion Segmentation for Biomedical Images with Single-step Reverse Process
Diffusion models have demonstrated their effectiveness across various generative tasks.
DumpKV: Learning based lifetime aware garbage collection for key value separation in LSM-tree
Key\-value separation is used in LSM\-tree to stored large value in separate log files to reduce write amplification, but requires garbage collection to garbage collect invalid values.
Exploring Low-Resource Medical Image Classification with Weakly Supervised Prompt Learning
The weakly supervised prompt learning model only utilizes the classes of images in the dataset to guide the learning of the specific class vector in the prompt, while the learning of other context vectors in the prompt requires no manual annotations for guidance.
Intensive Vision-guided Network for Radiology Report Generation
Given the above limitation in feature extraction, we propose a Globally-intensive Attention (GIA) module in the medical image encoder to simulate and integrate multi-view vision perception.
Contrastive Transformer Learning with Proximity Data Generation for Text-Based Person Search
Moreover, we propose a proximity data generation (PDG) module to automatically produce more diverse data for cross-modal training.
PGPointNovo: an efficient neural network-based tool for parallel de novo peptide sequencing
De novo peptide sequencing for tandem mass spectrometry data is not only a key technology for novel peptide identification, but also a precedent task for many downstream tasks, such as vaccine and antibody studies.
