Visual Large Model Series Camera

In 2025, relying on the camera big model technology system, linghtinbox will directly deploy the big model capability to the end side and launch a series of visual big model cameras.

The visual large model camera not only has better imaging quality, but more importantly, it has broken through bottlenecks such as weak scene universality and difficult recognition of complex targets, further improving the target detection rate, significantly reducing false alarms, and being able to recognize even with zero samples, resulting in a wider variety of detected target types.

Significantly reduce false positive detection rate and double improve accuracy rate

In practical applications, intelligent cameras can generate a large number of false alarms and warnings in different scenarios, lighting conditions, and weather conditions, resulting in increased operation and maintenance costs, poor user experience, and reduced trust in event response.

For over 20 years, Linghtinbox has been deeply involved in the video industry, combining rich industry knowledge from various scenarios to build pre trained large models. In the pre training stage, various real dynamic scene interference data, such as rain, snow, fog, strong light flashing, animal movement, vibration, etc., are added to enhance data under different conditions, greatly improving the detection and accuracy of intelligent recognition.

At the same time, Linghtinbox has established a comprehensive deployment technology system for large models, researching model structure design and quantification technology from the aspects of model lightweighting, computational efficiency improvement, and computational resource saving, and innovatively developing visual large model cameras that are more suitable for the scene.

In perimeter applications, linghtinbox has formed a ball machine IPC、 Multi camera and other large model surveillance series cameras. Compared to traditional video perimeter products, the large model surveillance series cameras further enhance recognition distance and reduce false alarm rates by over 90%. (Based on actual project measurement data). For example, in the same testing scenario, using a 4mm lens for testing, the visual large model camera can detect personnel intrusion at 70 meters, while traditional deep learning algorithms can detect it at 40 meters, and traditional smart algorithms can only detect it at 20 meters. Under the same detection conditions, when filtering false alarms of birds, traditional smart algorithms continue to detect bird invasions while detecting human invasions, while visual large model cameras can accurately filter false alarms of birds and only detect human invasions.

In traffic incident detection, Linghtinbox has launched visual model cameras such as integrated lightning vision machines, event detection cameras, and FOD lightning vision detection machines. In the field of highway traffic incident detection, it effectively solves the problem of false alarms and missed alarms of incidents such as littering, parking, and pedestrians in complex scenarios.

In the application of traffic checkpoints, visual large-scale camera products such as checkpoint capture units, non motorized vehicle capture units, and Leiyun ship checkpoint all-in-one machines have been launched. In the application of cabin feature recognition, when identifying seat belts, it effectively filters false alarms caused by low contrast, occlusion, complex postures, etc; Effectively filter out false alarms caused by lifting hands, gripping objects, etc. when making phone calls.

Support zero sample open recognition, with a wider variety of target recognition types

The implementation of traditional intelligent applications requires training tailored to the diverse needs of various industries and industries