Semantic segmentation is critical in medical image processing, with traditional specialist models facing adaptation challenges to new tasks or distribution shifts. While both generalist pre-trained ...
Most learning-based speech enhancement pipelines depend on paired clean–noisy recordings, which are expensive or impossible to collect at scale in real-world conditions. Unsupervised routes like ...
Introduction: Weeds compete with crops for water, nutrients, and light, negatively impacting maize yield and quality. To enhance weed identification accuracy and meet the requirements of precision ...
Abstract: Dental caries is a prevalent bacterial infection, and its early and accurate detection is essential for preventing irreversible damage to dental structures. Cone-beam computed tomography ...
Brain tumor segmentation is a vital step in diagnosis, treatment planning, and prognosis in neuro-oncology. In recent years, deep learning approaches have revolutionized this field, evolving from the ...
Dense Connection Decoder (DCD): A novel decoder architecture that leverages dense connections to enhance feature propagation and information flow. Layer-Aware Fusion: An innovative fusion strategy ...
First of all, I'd like to commend the authors on the excellent work presented in SSS! I have a quick question regarding the model architecture, specifically related to the frozen image encoder and ...
1 School of Electronic Information, Xijing University, Xi’an, China. 2 Department of Nuclear Medicine, Shaanxi Provincial Cancer Hospital, Xi’an, China. 3 Shaanxi University of Chinese Medicine, ...
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