Electronics and Telecommunications Research Institute

Soonyong Song

Hyunseok Kim

Young Sung Son

Myung Eun Kim

Jin Chul Choi

Donghun Lee

Seonghyun Kim

Jongkwon Son

Ingook Jang

Il Woo Lee

Geon Min Yeo

Seong Hee Park

Wun-Cheol Jeong

Young-Il Kim

Tae-Wook Heo

A method and an apparatus for exclusive reinforcement learning are provided, comprising: collecting information of states of an environment through the communication interface and performing a statistical analysis on the states using the collected information; determining a first state value of a first state among the states in a training phase and a second state value of a second state among the states in an inference phase based on analysis results of the statistical analysis; performing reinforcement learning by using one reinforcement learning unit of a plurality of reinforcement learning unit which performs reinforcement learnings from different perspectives according to the first state value; and selecting one of actions determined by the plurality of reinforcement learning unit based on the second state value and applying selected action to the environment.

Method and apparatus for reinforcement machine learning

An apparatus and method for abnormal situation detection are disclosed. An abnormal situation detection apparatus can map first sensor data among sensor data transmitted from a plurality of sensors into a vector value, convert it into first situation information in the form of an image pattern, and generate a learning model using the first situation information and an abnormal situation reference range. In addition, the abnormal situation detection apparatus can convert second sensor data among sensor data transmitted from a plurality of sensors into a form that can be input to the learning model, and determine whether an abnormal situation occurs by applying the converted second data to the learning model.

Apparatus and method for abnormal situation detection

In order to detect an unmanned aerial vehicle (UAV) in a monitoring area using a rotatable camera, an integrated sensor configures a first detection area in the monitoring area by rotating the camera after fixing the focal length of the camera to an initial value, and configures a second detection area in the monitoring area by rotating the camera after changing at least one of the focal length of the camera and a rotation path representing a distance from the origin of the monitoring area.

Method and apparatus for configuring detection area based on rotatable camera

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Sejong-si, South Korea

Soonyong Song