https://scholar.dgist.ac.kr/handle/20.500.11750/117 2026-04-05T15:52:52Z 2026-04-05T15:52:52Z 이형철 양현림 정철우 김민수 https://scholar.dgist.ac.kr/handle/20.500.11750/59189 2025-11-18T05:40:15Z

Title: DEVICE AND METHOD FOR CALCULATING STROKE VOLUME USING AI Author(s): 이형철; 양현림; 정철우; 김민수 Abstract: The present invention contains a stroke volume calculation device using AI, comprising: a filtering unit for filtering a stroke volume and an artery blood pressure value that are in a preset range, from first data and second data comprising a plurality of artery blood pressure values and a stroke volume corresponding to each artery blood pressure value; a pre-training unit for pre-training, by using third data filtered from the first data, a first stroke volume calculation model for calculating a stroke volume on the basis of the artery blood pressure value; a transfer learning unit for generating a second stroke volume calculation model by transfer learning, by using fourth data filtered from the second data, the first stroke volume calculation model for calculating a stroke volume on the basis of the artery blood pressure value; and a stroke volume calculation unit for calculating a stroke volume corresponding to inputted artery blood pressure of a specific patient by using the second stroke volume calculation model.

김민수 안규현 박힘찬 오세연 김진욱 https://scholar.dgist.ac.kr/handle/20.500.11750/57174 2025-07-25T02:42:22Z

Title: 그래프 처리 시스템 및 그래프 처리 시스템의 동작 방법 Author(s): 김민수; 안규현; 박힘찬; 오세연; 김진욱 Abstract: 일 실시예에 따른 그래프 처리 시스템은 위상 데이터 및 속성 데이터를 포함하는 그래프 데이터를 저장하는 적어도 하나의 보조 기억 장치, 그래프 데이터의 일부를 저장하는 메인 메모리, 메인 메모리로부터 수신한 그래프 데이터의 처리 및 동기화를 수행하는 코어들 및 장치 메모리들을 포함하는 복수의 그래픽 처리 장치들, 및 복수의 그래픽 처리 장치들에서 수행되는 그래프 데이터에 대한 질의 처리를 관리하고, 질의 처리 결과 중 갱신 가능한 속성 데이터를 적어도 하나의 보조 기억 장치에 저장하는 중앙 처리 장치를 포함한다.

임희철 김민수 https://scholar.dgist.ac.kr/handle/20.500.11750/46305 2025-07-25T04:08:02Z

Title: GPU 기반의 채널 단위 딥뉴럴 네트워크 구조 검색을 사용하는 인공지능 시스템 Author(s): 임희철; 김민수 Abstract: An artificial intelligence system and a method for searching for an optimal model are provided. A method for searching for a learning mode of an artificial intelligence system includes receiving, by an operator included in a first node, first channels, deriving, by the operator included in the first node, first parameter weight indexes corresponding to weights of first parameters by calculating the first parameters corresponding to each of the received first channels with the received first channels, generating and outputting a second channel group by combining the first channel with the other channel, receiving, by an operator included in a second node, second channels included in the second channel group, and deriving, by the operator included in the second node, second parameter weight indexes corresponding to weights of second parameters by calculating the second parameters corresponding to the received second channels with the received second channels.

남윤민 이성진 김민수 https://scholar.dgist.ac.kr/handle/20.500.11750/16893 2026-02-28T17:42:09Z

Title: 다항 조인 연산자를 이용한 쿼리 처리 방법 및 그 장치 Author(s): 남윤민; 이성진; 김민수