Abstract: The present disclosure according to at least one embodiment provides a method for performing a convolution operation. The method comprises dividing a filter of a convolution operation having a spatial domain size HF×WF into unit filters, while traversing a spatial domain of an input tensor of the convolution operation from an initial position thereof, repeating: i) obtaining an input patch having a size of HO×WO at a current position according to a result of the traversing, and ii) obtaining an output tensor corresponding to each unit filter as a result of a convolution operation between the obtained input patch and a unit filter of a position corresponding to a position of the obtained input patch, and accumulating the obtained output tensors respectively corresponding to the unit filters, thereby generating the output tensor of the convolution operation.

Abstract: An image recognition method includes: selecting an augmentation process from augmentation processes based on a probability table, in response to an acquisition of an input image; acquiring an augmented image by augmenting the input image based on the selected augmentation process; and recognizing an object from the augmented image based on a recognition model.

Abstract: An image recognition method includes: selecting an augmentation process from augmentation processes based on a probability table, in response to an acquisition of an input image; acquiring an augmented image by augmenting the input image based on the selected augmentation process; and recognizing an object from the augmented image based on a recognition model.

Abstract: A battery state estimating apparatus includes a learner configured to learn a battery state estimation model comprising a label corresponding to a battery state; and a state estimator configured to estimate a battery state of a target battery using the battery state estimation model.

Abstract: A battery state estimation apparatus includes a sensing data acquirer configured to acquire sensing data on a battery, and a battery state estimator configured to approximate the sensing data by mapping the sensing data to a predetermined feature space, and compare the approximated sensing data to predetermined reference information to estimate a state of the battery.

Abstract: A method and apparatus for detecting an abnormal state of a battery are provided. An entropy calculator is configured to calculate an information entropy based on battery estimation information and battery measurement information. The battery estimation information corresponds to an output required from the battery, and the battery measurement information is collected from the battery. A battery abnormality determiner is configured to determine whether the battery is in the abnormal state based on the information entropy.

Abstract: A method and an apparatus for monitoring battery state are provided. A method of monitoring battery state involves collecting vibration information based on a signal from an acceleration sensor, calculating a cumulative impact based on the vibration information, and estimating a degree of damage to a battery based on the cumulative impact.

Abstract: A method and an apparatus for monitoring battery state are provided. A method of monitoring battery state involves collecting vibration information based on a signal from an acceleration sensor, calculating a cumulative impact based on the vibration information, and estimating a degree of damage to a battery based on the cumulative impact.

Abstract: A method and an apparatus for monitoring battery state are provided. A method of monitoring battery state involves collecting vibration information based on a signal from an acceleration sensor, calculating a cumulative impact based on the vibration information, and estimating a degree of damage to a battery based on the cumulative impact.

Abstract: A method and an apparatus for estimating a state of a battery are provided. A received battery signal may be segmented into sets of segment data at a predetermined time interval, and a state of a battery may be estimated using an estimated battery state probability value of the segment data.

Abstract: A battery state estimating apparatus includes a learner configured to learn a battery state estimation model comprising a label corresponding to a battery state; and a state estimator configured to estimate a battery state of a target battery using the battery state estimation model.

Abstract: A battery state estimation apparatus includes a sensing data acquirer configured to acquire sensing data on a battery, and a battery state estimator configured to approximate the sensing data by mapping the sensing data to a predetermined feature space, and compare the approximated sensing data to predetermined reference information to estimate a state of the battery.

Abstract: A method and apparatus for detecting an abnormal state of a battery are provided. An entropy calculator is configured to calculate an information entropy based on battery estimation information and battery measurement information. The battery estimation information corresponds to an output required from the battery, and the battery measurement information is collected from the battery. A battery abnormality determiner is configured to determine whether the battery is in the abnormal state based on the information entropy.

Abstract: A method of authoring experiential learning content includes displaying an authoring window to author the experiential learning content when a request is made to author the experiential learning content; and creating a virtual world by loading and arranging 3D objects and a 2D objects, in the authoring window, which corresponds to a scenario of the experiential learning content. Further, the method includes defining an Action-zone that determines a position where a user is merged in the virtual world; and defining a state by dividing the scenario into a plurality of steps as time goes by based on the scenario to play the experiential learning content from a specific time point, respectively. Furthermore, the method includes defining a processing routine of an event occurred in the state; and authoring the experiential learning content according to the defined Action-zone, the defined state, and the defined processing routine.