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Found 4 papers, 4 papers with code
Predictive Accuracy-Based Active Learning for Medical Image Segmentation
Active learning is considered a viable solution to alleviate the contradiction between the high dependency of deep learning-based segmentation methods on annotated data and the expensive pixel-level annotation cost of medical images.
Pruner: An Efficient Cross-Platform Tensor Compiler with Dual Awareness
Tensor program optimization on Deep Learning Accelerators (DLAs) is critical for efficient model deployment.
H-DenseFormer: An Efficient Hybrid Densely Connected Transformer for Multimodal Tumor Segmentation
In this paper, we propose a hybrid densely connected network for tumor segmentation, named H-DenseFormer, which combines the representational power of the Convolutional Neural Network (CNN) and the Transformer structures.
DARNet: Dual-Attention Residual Network for Automatic Diagnosis of COVID-19 via CT Images
The ongoing global pandemic of Coronavirus Disease 2019 (COVID-19) poses a serious threat to public health and the economy.
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