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Spatial transcriptomics deconvolution at single-cell resolution using Redeconve
Computational deconvolution with single-cell RNA sequencing data as reference is pivotal to interpreting spatial transcriptomics data, but the...
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Deformable Spatial-Temporal Attention for Lightweight Video Super-Resolution
Video super-resolution (VSR) aims to recover high-resolution video frames from their corresponding low-resolution video frames and their adjacent...
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Research on the influence of different sampling resolution and spatial resolution in sampling strategy on landslide susceptibility map** results
Landslides, recognized as a significant global natural disaster, necessitate an exploration of the impact of various resolution types in sampling...
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SCS: cell segmentation for high-resolution spatial transcriptomics
Spatial transcriptomics promises to greatly improve our understanding of tissue organization and cell–cell interactions. While most current platforms...
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Inferring super-resolution tissue architecture by integrating spatial transcriptomics with histology
Spatial transcriptomics (ST) has demonstrated enormous potential for generating intricate molecular maps of cells within tissues. Here we present...
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Spatial resolution measurement method for 3D displays from contrast modulation
Augmented Reality 3D head-up displays use a autostereoscopic 3D display as a panel. The 3D optical unit of autostereoscopic 3D displays controls the...
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Spatial Resolution Evaluation Method Based on Edge Characteristics
The most common way to evaluate spatial resolution is visual method, but it is time-consuming, laborious, easily affected by evaluators and output...
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A novel spatial and spectral transformer network for hyperspectral image super-resolution
Recently, transformer networks based on hyperspectral image super-resolution have achieved significant performance in comparison with most...
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Spatial-Angular Decoupling Interaction Networks for Light Field Angular Super-Resolution
The light field image simultaneously captures both the intensity and directional information of light rays, making it a valuable tool for acquiring...
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Effect of landslide spatial representation and raster resolution on the landslide susceptibility assessment
The quality of landslide susceptibility assessment is effected by landslide inventory and raster resolution. The point landslide inventory and...
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A practical method for measuring planar spatial resolution with scatter on a CZT gamma camera
PurposeThis study proposes a practical method for evaluating 2D spatial resolution with scatter on a CZT planar detector gamma camera, which is...
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Spatial-Spectral Deep Residual Network for Hyperspectral Image Super-Resolution
Recently, single hyperspectral image super-resolution (SR) methods based on deep learning have been extensively studied. However, there has been...
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MFSRNet: spatial-angular correlation retaining for light field super-resolution
Light field (LF) images acquired by hand-held devices suffer from a trade-off between spatial and angular resolutions. To solve this problem,...
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Three-dimensional dipole orientation map** with high temporal-spatial resolution using polarization modulation
Fluorescence polarization microscopy is widely used in biology for molecular orientation properties. However, due to the limited temporal resolution...
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A high spatial resolution dataset of China’s biomass resource potential
Assessing biomass resource potential is essential for China’s ambitious goals of carbon neutrality, rural revitalization, and poverty eradication. To...
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Evaluating spatial resolution and imperfect detection effects on the predictive performance of inhomogeneous spatial point process models trained with simulated presence-only data
Species distribution models (SDMs) are crucial in ecology, conservation, and ecosystem management. Numerous SDMs have been developed over time, and...
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Deep learning-based approach for high spatial resolution fibre shape sensing
Fiber optic shape sensing is an innovative technology that has enabled remarkable advances in various navigation and tracking applications. Although...
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Enhancing spatial resolution in Fourier transform infrared spectral image via machine learning algorithms
Owing to the intrinsic signal noise in the characterization of chemical structures through Fourier transform infrared (FT-IR) spectroscopy, the...
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High-resolution alignment of single-cell and spatial transcriptomes with CytoSPACE
Recent studies have emphasized the importance of single-cell spatial biology, yet available assays for spatial transcriptomics have limited gene...
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SpiDe-Sr: blind super-resolution network for precise cell segmentation and clustering in spatial proteomics imaging
Spatial proteomics elucidates cellular biochemical changes with unprecedented topological level. Imaging mass cytometry (IMC) is a high-dimensional...
