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Found 3 papers, 1 papers with code
An Enhanced Encoder-Decoder Network Architecture for Reducing Information Loss in Image Semantic Segmentation
Experimental evaluations of our model demonstrate a substantial reduction in information loss and improved accuracy in semantic segmentation.
Efficiency optimization of large-scale language models based on deep learning in natural language processing tasks
The internal structure and operation mechanism of large-scale language models are analyzed theoretically, especially how Transformer and its derivative architectures can restrict computing efficiency while capturing long-term dependencies.
BCS-Net: Boundary, Context and Semantic for Automatic COVID-19 Lung Infection Segmentation from CT Images
The spread of COVID-19 has brought a huge disaster to the world, and the automatic segmentation of infection regions can help doctors to make diagnosis quickly and reduce workload.
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