Samsung Electronics Co., Ltd.

Kae Weon You

Sang Do Park

Jin Hee Jeon

Jun Haeng Lee

Young Jae Kim

Duk Jin Oh

Myung Hoon Kim

Kyoung Hoon Kang

Ji Ung Lee

Young Hak Lee

A deep learning device and system including the same is provided. The deep learning device comprising processing circuitry configured to determine whether a received image is abnormal using an anomaly detection model; merge at least some vectors extracted from the anomaly detection model; input, to a probability approximation model, principal components generated by a principal component analysis (PCA) to detect whether out of distribution (OOD) occurs in data of the received image; store a result of the determinations; and extract at least some the data in which the OOD occurs, as target labeling, using a target labeling extraction model when a rate of the data in which the OOD occurs is greater than or equal to a threshold value, wherein the anomaly detection model determines whether the received image is abnormal using the target labeling.

Deep learning device and system including the same

Provided are an apparatus and method for estimating a State of Health (SOH) of a battery, and an apparatus and method for generating an SOH estimation model. The apparatus for estimating an SOH of a battery includes a processor configured to divide sensed data of the battery into one or more regions; and estimate the SOH of the battery by applying different SOH estimation models to the one or more divided regions.

Apparatus and method for estimating state of health (SOH) of battery, and apparatus and method for generating SOH estimation model

A battery management apparatus and method to estimate a state of a battery is provided. The battery management apparatus includes a processor configured to collect battery information, to estimate a residual capacity of a battery at an operating temperature based on the collected battery information, to convert the estimated residual capacity of the battery into a capacity of the battery at a reference temperature, and to estimate a state of health (SOH) of the battery based on the converted capacity.

Battery management apparatus and method

The present disclosure is related to a battery management system which includes a location information obtainer configured to obtain location information of a battery, and an estimation model changer configured to change an estimation model to estimate an internal state of the battery according to a change in the location information.

Method and apparatus for battery management

Apparatuses and methods for estimating a state of a battery in a battery management system is provided. A battery management apparatus includes a rest period detector configured to detect a rest period of a battery, an environment information collector configured to collect environment information during the rest period, and a state of health (SOH) determiner configured to determine an SOH of the battery based on the collected environment information.

Growing community of inventors

Hwaseong-si, South Korea

Kae Weon You