Audience
System integrator, OEM, access control, traffic management
About Carmen Nano
Carmen® Nano is a software module designed to transform any IP camera into a powerful on-premise Automatic Number Plate Recognition (ANPR) and Make and Model Recognition (MMR) system. Optimized for NVIDIA® Jetson™-based devices, it leverages deep learning capabilities to deliver real-time, high-accuracy vehicle identification. Supporting over 38,000 plate types from more than 160 countries, Carmen® Nano ensures global applicability. Its flexible API allows seamless integration into existing systems, making it ideal for applications such as traffic monitoring, access control, and parking management.
Other Popular Alternatives & Related Software
Carmen FreeFlow
Carmen FreeFlow is a powerful, AI-driven automatic number plate recognition (ANPR) solution designed for high-speed, high-accuracy license plate reading across various applications, from traffic monitoring to tolling. Its robust performance in various lighting and weather conditions offers exceptional flexibility for free-flow traffic environments. Carmen FreeFlow supports various plate types and integrates seamlessly with existing systems, delivering real-time data and insights that enhance operational efficiency. It’s ideal for businesses seeking a scalable, reliable ANPR solution that adapts to dynamic traffic demands.
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Carmen GO
Carmen® GO is a plug-and-play Automatic Number Plate Recognition (ANPR) and Make and Model Recognition (MMR) software that transforms any IP camera stream into a rich data source. It accurately identifies vehicle license plates, makes, models, and colors from live and recorded video feeds. Supporting over 38,000 plate types across more than 160 countries, Carmen® GO offers global applicability. Its intuitive interface, embedded database, and REST API facilitate seamless integration into existing systems without extensive programming. It can process up to eight camera streams simultaneously and provides a scalable solution for traffic monitoring, parking management, and security applications.
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Carmen Worker
Carmen® Worker is an on-premise Automatic Number Plate Recognition (ANPR) software solution that delivers high-speed, real-time vehicle identification within your organization's infrastructure. Designed to operate independently of cloud services, it ensures complete data privacy and low-latency processing, making it ideal for applications requiring strict data control, such as access control, parking management, tolling, and traffic enforcement. Carmen® Worker supports license plate recognition for over 160 countries, covering more than 38,000 plate types, and integrates seamlessly with existing systems via its Vehicle API and Transport API, allowing for easy deployment across a wide range of infrastructure setups. The software is fully customizable, allowing for flexible configuration to meet the unique needs of each installation, from region-specific settings to parameter adjustments that maximize accuracy and efficiency in any operational environment.
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Carmen Cloud
Carmen® Cloud is a cloud-based Automatic Number Plate Recognition (ANPR) solution that leverages advanced machine learning algorithms to deliver high-accuracy license plate, vehicle make, model, and color recognition across over 200 countries. Its dynamic algorithms continually adapt, ensuring reliable identification in challenging conditions.
Designed for seamless integration, it offers a single API call to access ANPR, Make and Model Recognition (MMR), and Hazard Identification Number Recognition (ADR), simplifying deployment across various applications such as traffic monitoring, parking management, and security operations. Carmen® Cloud's scalable infrastructure accommodates fluctuating demands, providing instant insights without delays or bottlenecks.
Its global reach and deployment flexibility make it versatile for organizations seeking efficient and precise vehicle recognition capabilities.
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Pricing
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Company Information
Adaptive Recognition
Founded: 1991
Hungary
adaptiverecognition.com
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