Suspicious Shopping Behavior Detection

Suspicious Shopping Behavior Detection
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Scylla Suspicious Shopping Behavior Detection system detects suspicious shopping behavior that can result in shoplifting

Scylla is optimized to work on multiple video streams using a single GPU and provide real-time event tracking. Once an anomalous event has been recognized based on the series of frames given to the model, Scylla sends alerts to all assigned endpoints. The module supports real-time multiple stream processing as well as offline analysis of video recordings. The models are trained on a large amount of anomalous and normal videos which allows Scylla to operate in versatile environments and scenarios to immediately react and send alerts in case of an anomaly.

Scylla Suspicious Shopping Behavior Detection System features real-time detection of anomalous consumer behavior that may result in shoplifting in a centralized solution capable of handling multiple camera streams simultaneously, and with flexible deployment based on the customer’s choice (on-site, cloud-hosted, or on-edge)

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