Abstract: Deep learning models for medical image segmentation often struggle with task-specific characteristics, limiting their generalization to unseen tasks with new anatomies, labels, or modalities ...
This repository is the code implementation of the paper RSPrompter: Learning to Prompt for Remote Sensing Instance Segmentation based on Visual Foundation Model, which is based on the MMDetection ...
Semantic segmentation is a core task in computer vision, essential for applications requiring detailed scene understanding, such as medical imaging, precision agriculture, and remote sensing. Recent ...
Objective: To develop a deep learning (DL) model for carotid plaque detection based on CTA images and evaluate the clinical application feasibility and value of the model. Methods: We retrospectively ...
While running this example in Torch-TensorRT with 2.9.0 nightly branch, we get a segmentation fault. https://github.com/pytorch/TensorRT/tree/main/examples/torchtrt ...
The Black Friday Cyber Monday (BFCM) weekend is prime time for ecommerce businesses. But Black Friday is the day with the highest number of emails sent all year. And with fierce competition from ...
Model and clinical segmentation examples. (A) 71-year-old female with non-small cell lung cancer (NSCLC) from the internal test set. (B) 87-year-old male with NSCLC from the external test set. Both ...
Recent advances in deep learning have improved the segmentation accuracy of subcortical brain structures, which would be useful in neuroimaging studies of many neurological disorders. However, most ...
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