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Found 5 papers, 4 papers with code
FPL+: Filtered Pseudo Label-based Unsupervised Cross-Modality Adaptation for 3D Medical Image Segmentation
Adapting a medical image segmentation model to a new domain is important for improving its cross-domain transferability, and due to the expensive annotation process, Unsupervised Domain Adaptation (UDA) is appealing where only unlabeled images are needed for the adaptation.
Routing-Guided Learned Product Quantization for Graph-Based Approximate Nearest Neighbor Search
It suffers from the large-scale $\mathcal{X}$ because a PG with full vectors is too large to fit into the memory, e. g., a billion-scale $\mathcal{X}$ in 128 dimensions would consume nearly 600 GB memory.
PA-Seg: Learning from Point Annotations for 3D Medical Image Segmentation using Contextual Regularization and Cross Knowledge Distillation
The success of Convolutional Neural Networks (CNNs) in 3D medical image segmentation relies on massive fully annotated 3D volumes for training that are time-consuming and labor-intensive to acquire.
Navigable Proximity Graph-Driven Native Hybrid Queries with Structured and Unstructured Constraints
We easily deploy existing various PGs on this framework to process hybrid queries efficiently.
A Comprehensive Survey and Experimental Comparison of Graph-Based Approximate Nearest Neighbor Search
Approximate nearest neighbor search (ANNS) constitutes an important operation in a multitude of applications, including recommendation systems, information retrieval, and pattern recognition.
