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Average Ratings 0 Ratings

Total
ease
features
design
support

No User Reviews. Be the first to provide a review:

Write a Review

Description

Carmen® Worker is an on-site Automatic Number Plate Recognition (ANPR) software that provides rapid, real-time vehicle identification tailored to your organization's infrastructure. Built to function without reliance on cloud platforms, it guarantees total data confidentiality and minimal processing delays, making it well-suited for sectors that demand stringent data governance, including access control, parking oversight, toll collection, and traffic regulation. This software can recognize license plates from over 160 countries and accommodates more than 38,000 different plate designs, enabling seamless integration with current systems via its Vehicle API and Transport API for straightforward implementation across diverse infrastructure configurations. Moreover, Carmen® Worker is fully adaptable, offering customizable options to satisfy the specific requirements of each deployment, which includes regional settings and parameter tweaks that enhance precision and effectiveness in various operational contexts. Additionally, the software's flexibility makes it a preferred choice for organizations looking to improve operational workflows while maintaining high standards of data security.

Description

The NtechLab platform is designed to analyze video content, identifying human faces, bodies, actions, vehicles, and license plates with impressive precision. Utilizing advanced AI technology, it achieves exceptional speed and accuracy, setting new standards for recognition capabilities. The FindFace Multi system enhances this by offering multi-object recognition and analytical features, which are particularly beneficial for both public sector applications and various business needs. This technology enables swift and precise identification of faces, human forms, cars, and license plates in real-time video feeds or archived footage. Users can search through databases or archives not only by image samples but also by distinctive characteristics such as age, clothing color, or vehicle type. The dedicated team at NtechLab is continually refining these recognition algorithms to boost their effectiveness and precision further. With FindFace Multi, the process of detecting a face in live video, recognizing it, and finding a corresponding match in a vast database can be accomplished in under a second, making it an invaluable tool for real-time surveillance and analysis. Furthermore, this rapid response capability ensures that users can act promptly on the information gathered, enhancing security and operational efficiency.

API Access

Has API No 

API Access

Has API Yes 

Screenshots View All

No images available

Screenshots View All

Integrations

No details available.

Integrations

No details available.

Pricing Details

No price information available.
Free Trial Yes 
Free Version No 

Pricing Details

No price information available.
Free Trial Yes 
Free Version No 

Deployment

Web-Based No 
On-Premises Yes 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Customer Support

Business Hours Yes 
Live Rep (24/7) No 
Online Support Yes 

Customer Support

Business Hours Yes 
Live Rep (24/7) No 
Online Support Yes 

Types of Training

Training Docs Yes 
Webinars Yes 
Live Training (Online) Yes 
In Person Yes 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) Yes 
In Person Yes 

Vendor Details

Company Name

Adaptive Recognition

Founded

1991

Country

Hungary

Website

adaptiverecognition.com

Vendor Details

Company Name

NtechLab

Founded

2015

Country

Russia

Website

ntechlab.com/findface-multi/

Product Features

Computer Vision

Blob Detection & Analysis No 
Building Tools No 
Image Processing No 
Multiple Image Type Support No 
Reporting / Analytics Integration No 
Smart Camera Integration No 

Emotion Recognition

Facial Emotions No 
Facial Expression Analysis No 
Machine Learning No 
Photo Emotions No 
Speech Emotions No 
Video Emotions No 
Written Text Emotions No 

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