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Found 4 papers, 3 papers with code
GLIMS: Attention-Guided Lightweight Multi-Scale Hybrid Network for Volumetric Semantic Segmentation
Notably, GLIMS achieved this high performance with a significantly reduced number of trainable parameters.
Attention-Enhanced Hybrid Feature Aggregation Network for 3D Brain Tumor Segmentation
In our approach, we utilized a multi-scale, attention-guided and hybrid U-Net-shaped model -- GLIMS -- to perform 3D brain tumor segmentation in three regions: Enhancing Tumor (ET), Tumor Core (TC), and Whole Tumor (WT).
In-Bed Pose Estimation: A Review
Human pose estimation, the process of identifying joint positions in a person's body from images or videos, represents a widely utilized technology across diverse fields, including healthcare.
VIDI: A Video Dataset of Incidents
To assess the performance of the recent state-of-the-art approaches, Vision Transformer and TimeSformer, as well as to explore the contribution of video-based information for incident classification, we performed benchmark experiments on the VIDI and Incidents Dataset.
