Artificial intelligence (AI) is empowering various industries to greatly improve the quality and efficiency of critical applications and turn volumes of data into valuable business action. Among AI applications, computer vision is one of most popular applications for detecting obstacles, performing image segmentation, or extracting relevant context from a given scene. Similarly, video analysis allows for deeper situational understanding because sequences of images can provide new information about actions.
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With AI technologies being widely adopted in the railway industry to power next-generation intelligent rail applications, the AI-driven digital transformation is making railway operations safer, smarter and more reliable, significantly enhancing the passenger travel experience and freight logistics services. This session will introduce the status of AI adoption in the rail industry, typical AI-enabled applications, GPU-based AI solutions, and select use cases.
AI applications are gaining traction at the edge, promising performance, production, and efficiency gains for all walks of life. To ensure the successful implementation of AI applications at the edge, developers face a myriad of difficult choices from hardware, AI network, and framework options that may differ from application to application. In this session, ADLINK will address key considerations to developing a fully-fledged AI applications at the edge citing various industrial use cases and share tips to optimize AI implementation from day zero to post-deployment upgrade.
Robotics manufacturers can reduce their development effort and cost with ADLINK’s Robot Operating System (ROS) 2 Robotics solutions, combined with open-source software, like Open Robotics and Eclipse Cyclone DDS ROS middleware. Attend the webinar to learn how tool and module portfolios, and a ROS-compatible environment make it easy to develop applications across multiple hardware platforms, software packages, and service types.
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