使用Amazon Rekognition的公司
Amazon Rekognition is a service that makes it easy to add image analysis to your applications. With Rekognition, you can detect objects, scenes, and faces in images. You can also search and compare faces. Rekognition’s API enables you to quickly add sophisticated deep learning-based visual search and image classification to your applications.
使用Amazon Rekognition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\": [
\"amazon-rekognition\"
]
}"Technology
is any of
Amazon Rekognition
员工数13k收入$2.3BReal EstateAmazon Rekognition高置信度
员工数1.5M收入$3MIT Services and IT ConsultingAmazon Rekognition高置信度
员工数574收入$3MSoftware DevelopmentAmazon Rekognition高置信度
员工数146IT Services and IT ConsultingAmazon Rekognition高置信度
员工数942收入$19MIT Services and IT ConsultingAmazon Rekognition高置信度
员工数27IT Services and IT ConsultingAmazon Rekognition高置信度
员工数52Software DevelopmentAmazon Rekognition高置信度
员工数1kReal EstateAmazon Rekognition高置信度
员工数295Software DevelopmentAmazon Rekognition高置信度
员工数10Entertainment ProvidersAmazon Rekognition高置信度
我们拥有关于700家公司和用户使用Amazon Rekognition的数据。我们的Amazon Rekognition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 Amazon Rekognition 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。
Amazon Rekognition is a cutting-edge technology in the field of image analysis that leverages advanced machine learning algorithms to analyze images and videos. This powerful tool provides capabilities such as object recognition, facial analysis, scene understanding, text detection, and image moderation. By utilizing deep learning models, Amazon Rekognition enables developers and businesses to extract valuable insights from visual content, making it an essential component for various applications ranging from security and surveillance to content moderation and personalized user experiences.
Amazon Rekognition falls under the category of Image Analysis API, offering developers easy-to-integrate functionalities to analyze and extract information from images and videos. This technology allows businesses to automate tasks that traditionally require human intervention, streamlining processes and enhancing efficiency. With the ability to identify objects, people, scenes, and text within visual data, Amazon Rekognition empowers organizations to derive meaningful data insights and make data-driven decisions effectively.
Founded in 2016, Amazon Rekognition was developed by Amazon Web Services (AWS) with the aim of democratizing access to advanced image recognition capabilities. AWS recognized the increasing demand for image analysis tools across industries and sought to provide an easy-to-use solution that could be seamlessly integrated into existing applications. Since its inception, Amazon Rekognition has gained significant traction in the market, with a considerable market share within the Image Analysis API category. The technology's robust features and reliable performance have contributed to its popularity among developers and businesses alike.
Currently, Amazon Rekognition holds a substantial market share within the image analysis space, and its user base continues to grow as organizations recognize the value of leveraging visual data for various applications. With the growing importance of image analysis in diverse industries such as e-commerce, security, healthcare, and media, Amazon Rekognition is poised to maintain its market dominance and is expected to expand its influence in the future. As the demand for image analysis solutions increases, Amazon Rekognition is well-positioned to capitalize on this trend and further solidify its position as a leading technology in the field of image recognition and analysis.