In a world becoming ever more attuned to potential security threats, the need to deploy sophisticated surveillance systems is increasing. This article discusses inferencing a Microsoft Common Objects in Context (MS-COCO) detection model for detecting unattended baggage in a train station.
随着世界中面临的潜在安全威胁变得越来越多，企业对部署复杂的监控系统的需求开始不断增长。能够作为一个直观的“机器人眼睛”，准确实时地检测无人看管行李的智能系统，已经成为机场、火车站、商场和其他公共区域的安保人员的关键需求。本文介绍了用于火车站的无人看管行李检测的 Microsoft Common Objects in Context (MS-COCO) 检测模式。
Intel’s Excite project uses a combination of symbolic execution, fuzzing, and concrete testing to find vulnerabilities in sensitive code.
The Hadoop* Authentication Service helped Alibaba* improve the quality, performance and TCO of its cloud user identity information management system.