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Found 5 papers, 4 papers with code
Implicit Multi-Spectral Transformer: An Lightweight and Effective Visible to Infrared Image Translation Model
Initially, the Texture Mapping Module and Color Perception Adapter collaborate to extract texture and color features from the visible light image.
Dual-View Data Hallucination with Semantic Relation Guidance for Few-Shot Image Recognition
Specifically, an instance-view data hallucination module hallucinates each sample of a novel class to generate new data by employing local semantic correlated attention and global semantic feature fusion derived from base classes.
UWFormer: Underwater Image Enhancement via a Semi-Supervised Multi-Scale Transformer
Underwater images often exhibit poor quality, distorted color balance and low contrast due to the complex and intricate interplay of light, water, and objects.
ShaDocFormer: A Shadow-Attentive Threshold Detector With Cascaded Fusion Refiner for Document Shadow Removal
The STD module employs a traditional thresholding technique and leverages the attention mechanism of the Transformer to gather global information, thereby enabling precise detection of shadow masks.
Prediction of soft proton intensities in the near-Earth space using machine learning
The average correlation between the observed and predicted data is about 56%, which is reasonable in light of the complex dynamics of fast-moving energetic protons in the magnetosphere.
