닫기
Loading..

전자정보연구정보센터 ICT 융합 전문연구정보의 집대성

학술대회 프로시딩

홈 홈 > 연구문헌 > 학술대회 프로시딩 > 한국정보과학회 학술대회 > KCC 2020

KCC 2020

Current Result Document : 0 / 0

한글제목(Korean Title) 질의를 활용한 제로샷 객체 탐지
영문제목(English Title) Query-based zero-shot detection
저자(Author) 송호준   이강훈   장병탁   HoJoon Song   Ganghun Lee   Byoung-Tak Zhang  
원문수록처(Citation) VOL 47 NO. 01 PP. 0886 ~ 0888 (2020. 07)
한글내용
(Korean Abstract)
영문내용
(English Abstract)
The major development in object classification and detection models has already reached a point to where we can use deep learning models in real-life applications. However, there still exists the infamous drawback: large-scale annotated data are required for training. As such, zero-shot learning, predictions of data that has not been trained, is gathering attention in the machine learning community. In this paper, we propose a zero-shot detection method using a query-based model to detect untrained objects. The proposed method makes use of an extra image(the query) of the target object for the detection task. We verified the proposed method through experiments using handwritten characters. The results showed that the proposed method can successfully detect the bounding boxes of untrained objects.
키워드(Keyword)
원문 PDF 다운로드