Kognition
Kognition provides advanced AI-driven security technology that offers continuous, vigilant force multiplication at a fraction of the expense of conventional security solutions. Integrating seamlessly with existing systems, we empower organizations to actively detect threats (like weapon displays and crowd formation) and notify your security team about the presence of restricted individuals and VIPs. Kognition lowers IT expenditures and reduces the need for extra security personnel while enhancing incident response efficiency and delivering thorough security reporting and visibility for K-12+, commercial real estate, regulated sectors, and beyond.
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Ango Hub
Ango Hub is an all-in-one, quality-oriented data annotation platform that AI teams can use. Ango Hub is available on-premise and in the cloud. It allows AI teams and their data annotation workforces to quickly and efficiently annotate their data without compromising quality.
Ango Hub is the only data annotation platform that focuses on quality. It features features that enhance the quality of your annotations. These include a centralized labeling system, a real time issue system, review workflows and sample label libraries. There is also consensus up to 30 on the same asset.
Ango Hub is versatile as well. It supports all data types that your team might require, including image, audio, text and native PDF. There are nearly twenty different labeling tools that you can use to annotate data. Some of these tools are unique to Ango hub, such as rotated bounding box, unlimited conditional questions, label relations and table-based labels for more complicated labeling tasks.
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Prophesee Metavision
Metavision is a sophisticated software toolkit for event-based vision, created by Prophesee, that aims to streamline the assessment, design, and commercialization processes of event-based vision products. This software development kit (SDK) provides an extensive array of tools comprising 64 algorithms, 105 code examples, and 17 tutorials, which empower developers to create and implement event-driven applications effectively. With its open-source framework, the Metavision SDK promotes seamless compatibility between software and hardware components, nurturing a thriving community focused on event-based vision technologies. The toolkit encompasses a diverse array of computer vision disciplines, including machine learning, camera calibration, and high-performance applications. Developers benefit from a wealth of detailed documentation, amounting to over 300 pages of programming guides and reference materials, which lays a strong groundwork for product innovation. Furthermore, the Metavision SDK5 PRO version comes with enhanced features such as high-speed counting and spatter monitoring, among other advanced capabilities, elevating the potential for developers to create cutting-edge solutions. With such comprehensive resources at their disposal, users can confidently explore the possibilities of event-based vision technology.
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Viso Suite
Viso Suite stands out as the only comprehensive platform designed for end-to-end computer vision solutions. It empowers teams to swiftly train, develop, launch, and oversee computer vision applications without the necessity of starting from scratch with code. By utilizing Viso Suite, organizations can create top-tier computer vision and real-time deep learning systems through low-code solutions and automated software infrastructure. Traditional development practices, reliance on various disjointed software tools, and a shortage of skilled engineers can drain an organization's resources, leading to inefficient, underperforming, and costly computer vision systems. With Viso Suite, users can enhance and implement superior computer vision applications more quickly by streamlining and automating the entire lifecycle. Additionally, Viso Suite facilitates the collection of data for computer vision annotation, allowing for automated gathering of high-quality training datasets. It also ensures that data collection is managed securely, while enabling ongoing data collection to continually refine and enhance AI models for better performance.
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