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Found 5 papers, 0 papers with code
MEDBind: Unifying Language and Multimodal Medical Data Embeddings
Medical vision-language pretraining models (VLPM) have achieved remarkable progress in fusing chest X-rays (CXR) with clinical texts, introducing image-text data binding approaches that enable zero-shot learning and downstream clinical tasks.
GenFlow: Generalizable Recurrent Flow for 6D Pose Refinement of Novel Objects
Despite the progress of learning-based methods for 6D object pose estimation, the trade-off between accuracy and scalability for novel objects still exists.
Conversion of single-energy computed tomography to parametric maps of dual-energy computed tomography using convolutional neural network
Conclusions: SECT images were directly converted to the three parametric maps of DECT (i. e., VMIs, EAN, and RED).
Cross-Task Attention Network: Improving Multi-Task Learning for Medical Imaging Applications
Multi-task learning (MTL) is a powerful approach in deep learning that leverages the information from multiple tasks during training to improve model performance.
TMO: Textured Mesh Acquisition of Objects with a Mobile Device by using Differentiable Rendering
We present a new pipeline for acquiring a textured mesh in the wild with a single smartphone which offers access to images, depth maps, and valid poses.
