Advancing Hyperspectral and Multispectral Image Fusion: An Information-Aware Transformer-Based Unfolding Network

Advancing Hyperspectral and Multispectral Image Fusion: An Information-Aware Transformer-Based Unfolding Network

Information-aware Transformer Unfolding Network for Hyperspectral and Multispectral Image Fusion Background Introduction Hyperspectral images (HSIs) play a crucial role in remote sensing applications such as material identification, image classification, target detection, and environmental monitoring, due to their spectral information across multip...

A Graph-Neural-Network-Powered Solver Framework for Graph Optimization Problems

A Graph-Neural-Network-Powered Solver Framework for Graph Optimization Problems

A Framework for Solving Graph Optimization Problems Based on Graph Neural Networks Background and Research Motivation In solving Constraint Satisfaction Problems (CSPs) and Combinatorial Optimization Problems (COPs), a common method is the combination of backtracking and branch heuristics. Although branch heuristics designed for specific problems a...

Weakly Supervised Semantic Segmentation via Alternate Self-Dual Teaching

Weakly Supervised Semantic Segmentation via Alternate Self-Dual Teaching

Weakly Supervised Semantic Image Segmentation via Alternate Self-Dual Teaching Background Introduction With the continuous development of the computer vision field, semantic segmentation has become an important and active research direction. Traditional semantic segmentation methods rely on manually labeled pixel-level tags; however, obtaining thes...

Robust Multiobjective Reinforcement Learning Considering Environmental Uncertainties

Background In recent years, Reinforcement Learning (RL) has demonstrated its effectiveness in solving various complex tasks. However, many real-world decision-making and control problems involve multiple conflicting objectives. The relative importance (preference) of these objectives often needs to be balanced against each other in different scenar...

Modulating Effective Receptive Fields for Convolutional Kernels

GMConv: Adjusting the Effective Receptive Field of Convolutional Neural Networks Introduction Convolutional Neural Networks (CNNs) have achieved significant success in computer vision tasks, including image classification and object detection, through the use of convolutional kernels. However, in recent years, Vision Transformers (ViTs) have gained...

Dendritic-Cell-Targeting Virus-Like Particles as Potent mRNA Vaccine Carriers

Dendritic-cell-targeting Virus-like Particles as Potent mRNA Vaccine Carriers Introduction In vaccine development, especially mRNA vaccines, significant achievements have been made in recent years. The mRNA vaccines developed by Moderna and Pfizer/BioNTech against COVID-19 have set a successful precedent, greatly advancing the development of mRNA v...

A bilingual speech neuroprosthesis driven by cortical articulatory representations shared between languages

Bilingual Speech Neuroprosthesis Driven by Cortical Speech Representations Background In the development of neuroprostheses, research on decoding language from brain activity has primarily focused on decoding a single language. Thus, the extent to which bilingual speech production relies on unique or shared cortical activity between different langu...

Antibody-Displaying Extracellular Vesicles for Targeted Cancer Therapy

Antibody-Displaying Extracellular Vesicles for Targeted Cancer Therapy

The Application of Antibodies Displaying Extracellular Vesicles in Targeted Cancer Therapy Extracellular Vesicles (EVs) have been extensively researched as natural delivery carriers and mediators of biological signals in various tissues. In this study, researchers utilized these characteristics of EVs to demonstrate a modular delivery system for ca...

Imaging Bioluminescence by Detecting Localized Haemodynamic Contrast from Photosensitized Vasculature

Imaging Bioluminescence by Detecting Localized Haemodynamic Contrast from Photosensitized Vasculature

Academic News Report: New MRI Technology Achieves Biological Fluorescence Imaging by Detecting Local Hemodynamics of Photosensitive Blood Vessels Academic Background Introduction Bioluminescent probes are widely used for monitoring biomedical processes and cellular targets in living animals. However, the absorption and scattering of visible light b...

Spatial multi-omics at subcellular resolution via high-throughput in situ pairwise sequencing

Spatial multi-omics at subcellular resolution via high-throughput in situ pairwise sequencing

Spatial Multi-omics High Throughput In Situ Pairwise Sequencing at Subcellular Resolution Research Background and Objectives With the continuous advancement in biomedical research, the application of multi-omics technologies in understanding cell functions and disease mechanisms has gained increasing attention. However, many current in situ sequenc...