使用Kornia的公司
It is a differentiable computer vision library for PyTorch. It consists of a set of routines and differentiable modules to solve generic computer vision problems. At its core, the package uses PyTorch as its main backend both for efficiency and to take advantage of the reverse-mode auto-differentiation to define and compute the gradient of complex functions.
使用Kornia的公司列表
curl --request POST \
--url "https://api.theirstack.com/v1/companies/search" \
--header "Accept: application/json" \
--header "Content-Type: application/json" \
--header "Authorization: Bearer <api_key>" \
-d "{
\"company_technology_slug_or\": [
\"kornia\"
]
}"Technology
is any of
Kornia
员工数460Financial ServicesKornia高置信度
员工数3.1k收入$10MResearch ServicesKornia高置信度
员工数1.4k收入$248MSemiconductor ManufacturingKornia高置信度
员工数53Medical Equipment ManufacturingKornia中置信度
员工数63IT Services and IT ConsultingKornia中置信度
员工数1.8kSoftware DevelopmentKornia中置信度
员工数29Software DevelopmentKornia中置信度
员工数79Software DevelopmentKornia中置信度
员工数6.4kResearch ServicesKornia低置信度
员工数82k收入$19BHospitals and Health CareKornia低置信度
我们拥有关于19家公司和用户使用Kornia的数据。我们的Kornia用户和客户列表可供下载，并附有重要的公司信息，包括行业分类、组织规模、地理位置、融资轮次和收入数据等。
技术使用统计和市场份额
如何定位 Kornia 用户
- 如何自定义此列表？
您可以根据地理位置、行业、公司规模、收入、技术使用、职位发布等需求自定义此数据。您可以将数据下载为Excel或CSV格式。
- 如何在公司采用此技术时收到通知？
您可以为此数据设置提醒。您可以通过选择您感兴趣的技术开始，当有新公司使用该技术时，您将收到收件箱中的提醒。
- 如何将此数据导入我的CRM？
您可以将此数据导出为Excel文件，然后导入到您的CRM中。您也可以将数据导出到API。
常见问题
我们的数据来源于从数百万家公司收集的职位发布。我们监控公司网站、招聘网站和其他招聘平台上的这些发布。分析职位发布提供了一种可靠的方法来了解公司正在使用的技术，包括他们使用的内部工具。
我们每天刷新数据，以确保您访问的是最新的信息。这一频繁的更新过程保证了我们的洞察和情报反映行业的最新发展和趋势。
Kornia is an open-source differentiable computer vision library for PyTorch that implements a wide range of functionalities aimed at solving various tasks in the field of image processing and manipulation. It offers capabilities such as geometric transformations, color space operations, image filtering, and more, all of which can be seamlessly integrated into deep learning pipelines. Kornia's key feature lies in its ability to perform operations in a differentiable manner, making it ideal for tasks that involve optimization through gradient-based methods.
Image Processing and Management is the primary category to which Kornia belongs. Within this category, Kornia stands out as a versatile tool that caters to the needs of developers and researchers working on computer vision projects. By providing a comprehensive set of functions specifically designed for image processing, Kornia simplifies the implementation of complex algorithms and enables users to focus on the core aspects of their projects. Its integration with PyTorch also makes it a preferred choice for those already working in the deep learning domain.
Founded in 2019 by Edgar Riba, Kornia was created with the vision of bridging the gap between traditional computer vision techniques and modern deep learning frameworks. Motivated by the lack of a dedicated library that combined the benefits of both worlds, Riba set out to develop Kornia as a solution that would streamline the process of incorporating computer vision functionalities into deep learning models. Since its inception, Kornia has gained traction within the research community and is continuously evolving to meet the growing demands of the industry.
As of the latest market analysis, Kornia commands a modest market share within the Image Processing and Management category, with a steady growth trajectory projected for the future. With the increasing emphasis on computer vision applications across various industries, the demand for specialized tools like Kornia is expected to rise, driving its market penetration and adoption. As more developers recognize the value of Kornia in enhancing their image processing workflows, the technology is poised to expand its presence and solidify its position as a key player in the field.