2025年1月12日 · 对于HED和Sketch条件，CRS-Diff能够通过边界和轮廓信息实现直观的图像控制。 道路图和分割掩码条件提供了丰富的语义信息。 CRS-Diff生成的图像具有清晰的纹理细节和连贯的场景关系。 定量分析： 与ControlNet和Uni-ControlNet相比，CRS-Diff在SSIM、mIoU和FID指 …

2024年3月18日 · In this paper, we propose CRS-Diff, a new RS generative framework specifically tailored for RS image generation, leveraging the inherent advantages of diffusion models while integrating more advanced control mechanisms.

CRS-Diff, a new RS generative framework specifically tailored for RS image generation, leveraging the inherent advantages of diffusion models while integrating more advanced control mechanisms. Specifically, CRS-Diff can simultaneously support text-condition, metadata-condition, and image-condition control

2025年1月25日 · CRS, utilizing two synchronized laser pulses to enhance the Raman scattering signal coherently, offers millions of times of signal enhancement. A resonance occurs when the difference between the...

Coherent Raman scattering (CRS) microscopy is a chemical imaging modality that provides contrast based on intrinsic biomolecular vibrations. To date, endeavors...

2013年11月5日 · Imaging of deep crustal features from narrow-angle deep seismic reflection data, especially from fold belt region, has been a challenging task. The common reflection surface (CRS) stack is an alternative seismic imaging technique for multicoverage reflection data.

An ultrasonic atomizing device is used to realize quantitative two-dimensional sample addition, and a CCD camera is used to capture the CRS image.

2022年10月18日 · Export an image in GEE to open it in ArcGIS Pro. You are calling projection.transform as if the projection variable is a JavaScript literal object, but it is an Earth Engine server-side ee.Projection object whose properties …

2023年3月20日 · Coherent Raman scattering (CRS) microscopy is a chemical imaging modality that provides contrast based on intrinsic biomolecular vibrations. To date, endeavors on instrumentation have advanced CRS into a powerful analytical tool for studies of cell functions and in situ clinical diagnosis.

In this paper, we propose CRS-Diff, a new RS generative framework specifically tailored for RS image generation, leveraging the inherent advantages of diffusion models while integrating more advanced control mechanisms.