Bear Detector


The Bear Detector was created to detect bears for safety and forestry purposes. This algorithm localizes a variety of bear types including brown, black, grizzly, and polar bears, along with cubs. Built using proprietary CVEDIA synthetic technology, the Bear Detector distinguishes bears from common animals such as dogs, for usage along forestry trails, on farms, or on residential property.



CVEDIA | Bear DetectorCVEDIA | Bear DetectorCVEDIA | Bear DetectorCVEDIA | Bear DetectorCVEDIA | Bear Detector



PERFORMANCE

Optimized for edge performance with a low power profile.

RANGE

Up to 300 meters.

CONDITIONS

Dawn to dusk and artificial lightning.

ENVIRONMENT

Environmentally-agnostic performance.

ARCHITECTURE

Backbone: Resnet-101; Detector: RefineDet.

FUNCTIONALITY

Detection.

INPUT SIZE

512x512.

SENSOR MODALITY

Visible light and infrared.



Want to see our AI in action?

Book a demo now →



Our services


  • MAINTENANCE

Each CVEDIA model comes backed with an ongoing maintenance agreement. Our team is available for continuous improvements and to ensure upkeep.


  • FINE GRAIN CLASSIFICATION

Speak to our team to discuss model classification as a service add on or as a separate model. CVEDIA’s in-house team will work with you to define your requirements, and build a synthetic-based model incorporating your classification specifications.


  • ADDITIONAL CLASSES

CVEDIA models are built using proprietary synthetic data technology, meaning adding additional classes to your model is possible in a matter of weeks.

Use cases


  • PARKS AND FORESTRY

The Bear Detector can be used with simple and low-cost cameras to detect bears along park trails, in rural working environments, and on farms.


  • PROPERTY SECURITY

Use this algorithm to keep residential families and properties safe from bear intrusions using regular security cameras.


  • FARM SECURITY

Maintain safe and secure pastures for livestock and crops with the Bear Detector, with the ability to distinguish bears from common farm animals.