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Found 6 papers, 3 papers with code
Detail Matters: Mamba-Inspired Joint Unfolding Network for Snapshot Spectral Compressive Imaging
To address this issue, we propose a Mamba-inspired Joint Unfolding Network (MiJUN), which integrates physics-embedded DUNs with learning-based HSI imaging.
Transfer Learning in Vocal Education: Technical Evaluation of Limited Samples Describing Mezzo-soprano
Vocal education in the music field is difficult to quantify due to the individual differences in singers' voices and the different quantitative criteria of singing techniques.
UP-Diff: Latent Diffusion Model for Remote Sensing Urban Prediction
This study introduces a novel Remote Sensing (RS) Urban Prediction (UP) task focused on future urban planning, which aims to forecast urban layouts by utilizing information from existing urban layouts and planned change maps.
Context-Aware Integration of Language and Visual References for Natural Language Tracking
Tracking by natural language specification (TNL) aims to consistently localize a target in a video sequence given a linguistic description in the initial frame.
Adaptive-Mask Fusion Network for Segmentation of Drivable Road and Negative Obstacle With Untrustworthy Features
To provide a solution to this issue, we propose the Adaptive-Mask Fusion Network (AMFNet) by introducing adaptive-weight masks in the fusion module to fuse features from RGB and depth images with inconsistency.
GA-HQS: MRI reconstruction via a generically accelerated unfolding approach
Deep unfolding networks (DUNs) are the foremost methods in the realm of compressed sensing MRI, as they can employ learnable networks to facilitate interpretable forward-inference operators.
