The correct answer is A) Response skills for possible local hazards, such as hurricanes or avalanches.
The CERT Program trains community volunteers in basic fire safety, light search and rescue, and disaster medical operations. What else might a CERT volunteer learn during CERT Basic Training?
Answer:
Response skills for possible local hazards, such as hurricanes or avalanches.
CERT stands for Community Emergency Response Team. This is an important program under the Citizen Corps, established by the Homeland Security Department.
The members are volunteers and receive proper instruction on how to prevent and react before difficult times or natural disasters. That is why it is important that CERT do community work to inform and teach the community about basic procedures that can keep them safe.
Answer: Although many factors combine to influence weather, the four main ones are solar radiation, the amount of which changes with Earth's tilt, orbital distance from the sun and latitude, temperature, air pressure and the abundance of water.
Explanation: am i wrong
Markerless motion capture and understanding of professional non-daily human movements is an important yet unsolved task, which suffers from complex motion patterns and severe self-occlusion, especially for the monocular setting. In this paper, we propose SportsCap -- the first approach for simultaneously capturing 3D human motions and understanding fine-grained actions from monocular challenging sports video input.
About SportCaps :
SportsCap proposes a challenging sports dataset called Sports Motion and Recognition Tasks (SMART) dataset, which contains per-frame action labels, manually annotated pose, and action assessment of various challenging sports video clips from professional referees.
Their approaches :
This is especially prevalent in non-daily action classes like fitness and sports domains. This can be mitigated, for example, by annotating domain-specific datasets , but that requires a considerable amount of manual annotation efforts, financial resources, and 3D annotations can only be obtained in controlled conditions. Therefore, we propose to learn domain-specific pose-sensitive representations from unlabeled videos, which can be fine tuned using only a small labeled dataset. ...
Learn more about Monocular 3 D Human :
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