05-08-2022, 05:11 AM
Russia’s Defense Ministry said that it was using “high-precision weapons” to disable military infrastructure, air defense facilities, military airfields and Ukrainian army planes, Russia’s state-run RIA Novosti news agency reported. The Ukrainian authorities said that invading naval forces were coming ashore at multiple points, including in Kharkiv and the southern city of Kherson. Three emergency workers were injured when a command post was struck by shelling in Nizhyn, in the north, and six people were trapped under rubble when the city’s airport came under attack, Ukraine’s Interior Ministry reported. Military depots, warehouses and National Guard were hit with artillery blasts, the ministry said. As dawn broke in Kyiv, Mr. Zelensky of Ukraine said he had declared martial law. But the army was under siege. Seeking to capture the entire territories of Donetsk and Luhansk, which Mr. Putin recognized as independent on Monday, the rebels were “using all weapons at their disposal,” the Russian news media reported. However, many of these applications have real-world constraints that have yet to be addressed properly, such as the need for an on-the-edge end-to-end system to meet privacy and scalability concerns and real-time latency constraints. These real-world constraints inhibit the deployment of existing skeleton-based action recognition works. Existing works that focus on skeleton-based action recognition often assume ideal conditions that are not representative of the real-world context. Typically, the pose information used by the network is assumed to be perfect and is often based on hand-annotated data. However, in the case of a real-world system, skeletal pose information would come from an imperfect human pose estimator, leading to imperfect pose data. The accuracy of these pose estimators is further hampered by the resource constraints of edge devices. Additionally, these works often neglect satisfying the latency constraints of these real-world applications on edge devices, which decidedly limits their suitability towards real-world use. dunbar's number
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