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Found 7 papers, 2 papers with code
Medical Multimodal Foundation Models in Clinical Diagnosis and Treatment: Applications, Challenges, and Future Directions
Recent advancements in deep learning have significantly revolutionized the field of clinical diagnosis and treatment, offering novel approaches to improve diagnostic precision and treatment efficacy across diverse clinical domains, thus driving the pursuit of precision medicine.
Temporal Consistency Learning of inter-frames for Video Super-Resolution
A spatio-temporal stability module is designed to learn the self-alignment from inter-frames.
Dense residual Transformer for image denoising
In this paper, we proposed an image denoising network structure based on Transformer, which is named DenSformer.
RefineCap: Concept-Aware Refinement for Image Captioning
Automatically translating images to texts involves image scene understanding and language modeling.
Ranked #27 on
Image Captioning
on COCO Captions
Neural Text Classification by Jointly Learning to Cluster and Align
Distributional text clustering delivers semantically informative representations and captures the relevance between each word and semantic clustering centroids.
COVID-19 Chest CT Image Segmentation -- A Deep Convolutional Neural Network Solution
Inspired by the observation that the boundary of the infected lung can be enhanced by adjusting the global intensity, in the proposed deep CNN, we introduce a feature variation block which adaptively adjusts the global properties of the features for segmenting COVID-19 infection.
Highway Transformer: Self-Gating Enhanced Self-Attentive Networks
Self-attention mechanisms have made striking state-of-the-art (SOTA) progress in various sequence learning tasks, standing on the multi-headed dot product attention by attending to all the global contexts at different locations.
