Look up the most recent CRS tag in Docker Hub (runtime-sensor) - https://hub.docker.com/r/qualys/runtime-sensor. Use the latest Qualys Container Runtime Sensor image - qualys/runtime-sensor:latest - from Dockerhub.

2020年6月8日 · Earth Engine generates reduced-resolution versions of each image when it is ingested. Part of the upload process involves specifying how the reduced-resolution pixels should be derived -- "mean" is the most common answer, but …

Some of the functional implementations of remote sensing imagery refer to: GeoSeg, Txt2Img-MHN and SGCN. Sincere thanks to their excellent work! title={Crs-diff: Controllable remote sensing image generation with diffusion model}, author={Tang, Datao and Cao, Xiangyong and Hou, Xingsong and Jiang, Zhongyuan and Liu, Junmin and Meng, Deyu},

Learn the basics of coordinate reference systems (CRS) or projections for spatial raster data. We also cover how to transform CRS using rasterio and geowombat.

ModSecurity CRS Docker 项目是一个官方的 Docker 镜像，结合了 ModSecurity 和 OWASP Core Rule Set (CRS)。 ModSecurity 是一个开源的、跨平台的 Web 应用防火墙 (WAF)，支持 Apache、IIS 和 Nginx 等 Web 服务器。 OWASP CRS 是一组通用的攻击检测规则，用于与 ModSecurity 或其他兼容的 Web 应用防火墙一起使用。 该项目的主要编程语言是 Shell 脚本 和 Dockerfile，用于构建和管理 Docker 镜像。 1. Docker 环境未正确配置. 问题描述： 新手在使 …

2022年10月18日 · I used the following script to export an image from Earth Engine. I am trying to specify the crs_transform parameter argument in the Export.image.toDrive function using the "transform" pr...

2024年3月23日 · 有时常见的像元倾斜的数据可能是 SR-ORG：6974 坐标系（例如 MOD09A1 数据集），这时需要重投影转换为地理坐标。 SR-ORG:6974 是许多 MODIS 遥感影像 产品使用的一种全球正弦投影，属于投影坐标系。 需要转换为墨卡托投影（Mercator projection），从而消除上述像元倾斜的状态。 "EPSG:4326" 参数是 WGS1984 地理坐标系。 批量 查看、判断Collection中每张 image 的分辨率： var feat = ee. Feature (ee. Geometry. Point ([0, 0])) // 在函数内创建.

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.

The owasp/modsecurity-crs container images in their default configuration (i.e., without manual changes to / overrides of configuration files) act as reverse proxies and require a running backend at the address specified through the BACKEND environment variable.

In this article, 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.