Cloudastructure
Allows for a live, unified view of multiple sites on any device. History can be retrieved up to 10x faster that traditional on-premises systems. The first cloud-native platform for video surveillance with AI and computer vision analytics. This platform provides better and more cost-effective enterprise protection. Security risks eliminated, no video or data are stored or accessed over the network. It is possible to significantly reduce IT server management costs and maintenance costs when compared to hybrid or on-premises systems. Site management is simplified and can be centralized. Scales to unlimited locations and cameras. Cloud video surveillance systems can be easily managed, used, and installed. Setup is easy thanks to the user-friendly interface. You don't need any technical skills. Advanced vehicle and person detection, counting, classifications, license plate recognition, wrong way detection, etc. Search by social distance violation to find out how many people are located in space and their distance.
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FindFace
NtechLab platform processes video, recognizes faces, bodies, actions, cars, and plate numbers. AI-powered technology allows for record breaking accuracy and speed of recognition. FindFace Multi's multi-object and analytic capabilities open up new possibilities for addressing public sector and business challenges. FindFace Multi recognizes faces, bodies, cars, license plates, and other information in live video streams or archives. You can search for faces, bodies, or vehicles in a database, or in an archive, using a photo sample or by specific features, such as age, clothing color, vehicle model, or gender. NtechLab developers continue to improve recognition algorithms, increasing their accuracy and performance. It takes less than a second for FindFace Multi to recognize a face in a stream of video and then search for it in a database that contains billions of images.
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Google Cloud Vision AI
AutoML Vision provides insights from images at the edge and cloud. Pre-trained Vision API models can also be used to understand text and detect emotion. Google Cloud offers two computer vision products, which use machine learning to help understand your images with an industry-leading prediction accuracy. Automate the creation of custom machine learning models. Upload images, train custom image models using AutoML Vision's intuitive graphical interface, optimize your models for accuracy and latency, and export them to your cloud application or to a range of devices at the edge. Google Cloud's Vision API provides powerful pre-trained machine-learning models via REST and RPC APIs. Assign labels to images and classify them quickly into millions of predefined groups. Detect faces and objects, read printed and handwritten texts, and add valuable metadata to your image catalog.
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Plainsight
Our vision AI platform was built from the ground up to simplify your machine learning projects. It allows you to develop video analytics applications quickly and effectively. Plainsight is a platform that allows you to quickly create vision AI-powered solutions across all industries. It's easy to use and doesn't require any code. One interface allows you to connect, manage, and control sensors, cameras, and edge devices. To provide a high-quality foundation for models, collect accurate training datasets. Smart polygon selection, predictive labeling, and automated object recognition can accelerate labeling. A breakthrough process that reduces the time it takes to create AI solutions for vision is able to quickly train models. Rapidly deploy and scale applications on-premises, in the cloud, or at the edge to meet your business needs.
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