최소 단어 이상 선택하여야 합니다.
최대 10 단어까지만 선택 가능합니다.
다음과 같은 기능을 한번의 로그인으로 사용 할 수 있습니다.
NTIS 바로가기한국산업정보학회논문지 = Journal of the Korea Industrial Information Systems Research, v.26 no.5, 2021년, pp.1 - 9
임지연 (한국원자력연구원 미래전략본부 인공지능응용전략실) , 이성옥 (주식회사 TnF.AI) , 김경표 (한국원자력연구원 한사우디원자력공동연구센터) , 유용균 (한국원자력연구원 미래전략본부 인공지능응용전략실)
Children's drawings are widely used in the diagnosis of children's psychology as a means of expressing inner feelings. This paper proposes a children's drawings-based object detection algorithm applicable to children's psychology analysis. First, the sketch area from the picture was extracted and th...
Korea Youth Counseling & Welfare Institute (2020). Daily life changed by COVID-19 and Investigation and countermeasures for the perception of adolescent guardians, Youth Counseling Issue Paper, 2, 1-14.
Jo, S. H. (2020). [Measures for Prevention of Abuse of Children and Adolescents] Contents and Future Plans, Parenting Policy Forum, 28-33
Center for Transnational Migration and Social Inclusion (2021). Childcare during Covid-19 and Mental Health Crisis for Parents, Issue Brief Series on Impact of Covid-19 on Care.
Barak, A. (2011). Internet-based psychological testing and assessment. In: Online Counseling. Academic Press, 225-255.
Mattson, D. C. (2015). Usability assessment of a mobile app for art therapy. The Arts in Psychotherapy.
Yoon, Y. I. (2015). The childrens HTP test application development based on mobile device. Design convergence study, 14, 293-310.
Kim, S. K., & Yu, K. (2021). Development of Fuzzy Reasoning based Psychological Diagnosis Application with Automatic Hand-drawing Analysis. Journal of Digital Contents Society, 22(3), 519-525.
Park, J., Shin, S., Kim, J. Y., Park, K. H., Lee, S., Jeon, M., Kim, S. (2019). Preliminary Research of HTP Sentiment Analysis Automation on Children's Drawings. The HCI Society of Korea conference, 867-871.
Ren, S., He, K., Girshick, R., & Sun, J. (2015). Faster r-cnn: Towards real-time object detection with region proposal networks. Advances in neural information processing systems, 28, 91-99.
Girshick, R., Donahue, J., Darrell, T., & Malik, J. (2014). Rich feature hierarchies for accurate object detection and semantic segmentation. In Proceedings of the IEEE conference on computer vision and pattern recognition, 580-587.
Girshick, R. (2015). Fast r-cnn. In Proce dings of the IEEE international conference on computer vision, 1440-1448.
Everingham, M., Van Gool, L., Williams, C. K., Winn, J., & Zisserman, A. (2010). The pascal visual object classes (voc) challenge. International journal of computer vision, 88(2), 303-338.
Pizer, S. M., Amburn, E. P., Austin, J. D., Cromartie, R., Geselowitz, A., Greer, T., ... & Zuiderveld, K. (1987). Adaptive histogram equalization and its variations. Computer vision, graphics, and image processing, 39(3), 355-368.
Y. Wu, A. Kirillov, F. Massa, W.-Y. Lo, and Girshick R. (2019). "Detectron2," https://github.com/facebookresearch/detectron2
Otsu, N. (1979). A threshold selection method from gray-level histograms. IEEE transactions on systems, man, and cybernetics, 9(1), 62-66.
Howse, J. (2013). OpenCV computer vision with python. Birmingham: Packt Publishing.
*원문 PDF 파일 및 링크정보가 존재하지 않을 경우 KISTI DDS 시스템에서 제공하는 원문복사서비스를 사용할 수 있습니다.
Free Access. 출판사/학술단체 등이 허락한 무료 공개 사이트를 통해 자유로운 이용이 가능한 논문
※ AI-Helper는 부적절한 답변을 할 수 있습니다.