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Deep Learning Based Face Recognition and Alarm Management Software
Fra Milestone Systems
Corvo Identify - Deep Learning Based Face Recognition and Alarm Management SoftwareCorvo® Identify provides the highest accuracy rate through the use of deep learning-based technology. Its enhanced capabilities include fast face detection, advanced face tracking and high accurate face recognition to identify persons of interest, criminals, missing persons and VIPs from photos, cameras and archived videos.
Corvo Identify’s advanced technology works under uncontrolled, real-life conditions. The system overcomes real-life challenges which frequently constrain most of the face recognition algorithms; such as pose, age and illumination variations. With its advanced face recognition engine, Corvo is
robust to exaggerated expressions, occlusions, eyeglasses, hats and scarfs too.
Corvo Identify Corporate enables highly scalable software for mission-critical and large scale (1M+ face enrollments, hundreds of cameras and multi-users) systems. Corvo eliminates single points of failure through its distributed and fault-tolerant software architecture.
- Real-time alarms through cameras
- Searching suspects from face detection history
- Suspect investigation from photos and archived videos
- Smart alarm dispatch and easy alarm verification
- ONVIF Profile S compliance etc.
IndustriesAirports Arts & Entertainment City Surveillance Critical Infrastructure Education Finance & Insurance Healthcare Public Transport Retail Seaports
Area of practiceAccess Control Analytics Biometrics Central Monitoring Cloud and Managed Services Forensic enhancement Fraud Incident management Investigation Law Enforcement Smart City Software as a Service (Saas) Surveillance Transportation Video verification
ChallengesControl access to restricted areas Find lost children Gather evidence for criminal investigations Provide a personalized customer experience Provide evidence against injury lawsuits Provide situational awareness to response teams
Where it is used?
Face Recognition System for Homeland SecurityCorvo Identify central face recognition and alarm management software is used for homeland security.
G20 Antalya Summit Mobile Face Recognition SystemTurkish National Police preferred Nevalabs to secure the G20 Antalya Summit.
How to install
This is where you can find additional documentation
|XProtect-Corvo Identify Integration Installation Guide||pdf Download (2,82 MB)|
|XProtect-Corvo Identify Integration User Guide||pdf Download (4,44 MB)|
|XProtect-Corvo Identify Integration Brochure||pdf Download (199,85 KB)|
|Nevalabs Brochure||pdf Download (650,55 KB)|
Here you can find more information about installers and installation guides
Has proven compatibility with the following Milestone versions:
XProtectExpert2019 R3, 10.08 2019
XProtectEssential+2019 R2, 06.19 2019
XProtectProfessional+2019 R3, 10.08 2019
Is also expected to work with:
XProtectExpert2019 R1, 02.05 2019 og senere
XProtectEssential+2019 R3, 01.01 0001 og senere
XProtectProfessional+2019 R1, 02.05 2019 og senere
Your location is: De forente stater
- South Africa
- Hong Kong
- Korea, Republic of
- Saudi Arabia
- Sri Lanka
- United Arab Emirates
- Aland Islands
- Bosnia and Herzegovina
- Czech Republic
- Faroe Islands
- Isle Of Man
- Netherlands Antilles
- San Marino
- Svalbard And Jan Mayen
- United Kingdom
- Costa Rica
- Dominican Republic
- United States
- French Polynesia
- New Zealand
- Puerto Rico
- El Salvador
- French Guiana
Language versions available
Provide a personalized customer experience
Retails are constantly searching for new and innovative ways to serve their customers. Business intelligence services, mobile apps, IoT tech and customer segmentation tools and other customer service technologies can help create more personalized customer experiences.
Provide evidence against injury lawsuits
Legal teams need good systems in place to find evidence and share it with the right people. For example, they may need to review video footage that shows the moment a worker receives an injury – and what that worker was doing at that time. This critical evidence can be the proof that legal teams need to prove fault in the case of an injury lawsuit.
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