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권호기사 목록 테이블로 기사명, 저자명, 페이지, 원문, 기사목차 순으로 되어있습니다.
기사명 저자명 페이지 원문 목차
3D 행동 유도장 기반 대규모 에이전트 행동 시뮬레이션 = 3D affordance field based crowd agent behavior simulation 옥수열, 한명우, 이석환 p. 629-641
(An) automatic strabismus screening method with corneal light reflex based on image processing Xi-Lang Huang, Chang Zoo Kim, Seon Han Choi p. 642-650
딥러닝을 통한 문서 내 표 항목 분류 및 인식 방법 = Methods of classification and character recognition for table items through deep learning 이동석, 권순각 p. 651-658
Multi-human behavior recognition based on improved posture estimation mode Zhang Ning, Park Jin-Ho, Lee Eung-Joo p. 659-666
Diagnosis of Alzheimer's disease using combined feature selection method Fazal Ur Rehman Faisal, Uttam Khatri, Goo-Rak Kwon p. 667-675
측위 안정화를 위한 End to End 기반의 Wi-Fi RTT 네트워크 구조 설계 = End-to-end-based Wi-Fi RTT network structure design for positioning stabilization 성주현 p. 676-683
휴지기 기능적 자기공명영상의 독립성분분석기법 기반 내정상태 네트워크 기능 연결성과 확산텐서영상의 트랙토그래피 기법을 이용한 구조 연결성의 통합적 분석 = Combined analysis using functional connectivity of default mode network based on independent component analysis of resting state fMRI and structural connectivity using diffusion tensor imaging tractograph 최혜정, 장용민 p. 684-694
Research on shellfish recognition based on improved faster RCNN Yiran Feng, Sang-Yun Park, Eung-Joo Lee p. 696-700
Human face recognition based on improved CNN model with multi-layers Ruyang Zhang, Eung-Joo Lee p. 701-708
예능프로그램의 부캐릭터 전략 연구 : A study on the strategy of sub-character in entertainment programs <Hang Out With Yoo> / <놀면 뭐하니?>를 중심으로 이의정, 이종훈 p. 709-716
게임상의 Zombie Character 인지속성에 관한 연구 = Research for the cognitive properties of zombie game character 이금준, 조동민 p. 717-726
미술관 애플리케이션의 인터랙션 요소 및 감성디자인에 관한 연구 : A study on the interaction elements and emotional design of art museum applications : focusing on application art keys / 애플리케이션 아트키를 중심으로 후천위안, 안병진, 이병국 p. 727-735
민화와 풍속화를 이용한 AI 기반의 콘텐츠 원천 데이터 생성 모델의 연구 = A study of an AI-based content source data generation model using folk paintings and genre paintings 양석환, 이영숙 p. 736-743

참고문헌 (25건) : 자료제공( 네이버학술정보 )

참고문헌 목록에 대한 테이블로 번호, 참고문헌, 국회도서관 소장유무로 구성되어 있습니다.
번호 참고문헌 국회도서관 소장유무
1 S.A. Haidar, S. Akihiko, K. Hitoshi, I. Ryuta, I. Manabu, and T. Kenji, “Machine Learning for Diagnosis of AD and Prediction of MCI Progression From Brain MRI Using Brain Anatomical Analysis Using Diffeomorphic Deformation,” Frontiers in Neurology, Vol. 11, pp. 1894, 2021. 미소장
2 E. Lella, N. Amoroso, A. Lombardi, T. Maggipinto, S. Tangaro, R. Bellotti et al., “Communicability Disruption in Alzheimer’s Disease Connectivity Networks,” Journal of Complex Networks, Vol. 7, pp. 83-100, 2019. 미소장
3 S. ARB Rombouts, F. Barkhof, R. Goekoop, C.J. Stam, and P. Scheltens, “Altered Resting State Networks in Mild Cognitive Impairment and Mild Alzheimer's Disease: an fMRI Study,” Human Brain Mapping, Vol. 26, No. 4 pp. 231-239, 2005. 미소장
4 X. Zhao, Y. Liu, X. Wang, B. Liu, Q. Xi, Q. Guo et al., “Disrupted Small-world Brain Networks in Moderate Alzheimer's Disease: a Resting-State fMRI Study,” PloS One, Vol. 7, No. 3, pp. e33540, 2012. 미소장
5 E. Lella, N. Amoroso, A. Lombardi, T. Maggipinto, S. Tangaro, and R. Bellotti, “Communicability Disruption in Alzheimer’s Disease Connectivity Networks,” Journal of Complex Networks, Vol. 7, Issue 1, pp. 83-100, 2019. 미소장
6 F. Al-Turjman, M.H. Nawaz, and U.D. Ulusar, “Intelligence in the Internet of Medical Things era: A Systematic Review of Current and Future Trends,” Computer Communications, Vol. 150, pp. 644-660, 2020. 미소장
7 J.A.M. Sidey-Gibbons and C.J. Sidey-Gibbons, “Machine Learning in Medicine: a Practical Introduction,” BMC Medical Research Methodology, Vol. 19, pp. 1-18, 2019. 미소장
8 M.I. Jordan and T.M. Mitchell, “Machine Learning: Trends, Perspectives, and Prospects,”Science, Vol. 349, Issue 6245, pp. 255-260, 2015. 미소장
9 9 ] C. Casalino, G. Castellano, A. Consiglio, M. Liguori, N. Nuzziello, and D. Primiceri. “A Predictive Model for Microrna Expressions in Pediatric Multiple Sclerosis Detection,” International Conference on Modeling Decisions for Artificial Intelligence, Springer, pp. 177-188, 2019. 미소장
10 M.T. Angelillo, F. Balducci, D. Impedovo, G. Pirlo, and G. Vessio. “Attentional Pattern Classification for Automatic Dementia Detection,”IEEE Access, Vol. 7, pp. 57706-57716, 2019. 미소장
11 S. Bhattacharjee, D. Pakash, H.C. Kim, and H.K. Choi, “Multichannel Convolution Neural Network Classification for the Detection of Histological Pattern in Prostate Biopsy Images,”Journal of Korea Multimedia Society, Vol. 23, No. 12, pp. 1486-1495, 2020. 미소장
12 M. Dyrba, M. Ewers, M. Wegrzyn, I. Kilimann, C. Plant, A. Oswald et al., “Robust Automated Detection of Microstructural White Matter Degeneration in Alzheimer’s Disease Using Machine Learning Classification of Multicenter DTI Data,” PloS One, Vol. 8, No. 5, pp. e64925, 2013. 미소장
13 E. Lella, N. Amoroso, R. Bellotti, D. Diacono, M. La Rocca, T. Maggipinto et al., “Machine Learning for the Assessment of Alzheimer's Disease through DTI,” Applications of Digital Image Processing XL, International Society for Optics and Photonics, Vol. 10396, pp. 1039619. 2017. 미소장
14 C. Lian, M. Liu, J. Zhang, and D. Shen. “Hierarchical Fully Convolutional Network for Joint Atrophy Localization and Alzheimer's Disease Diagnosis Using Structural MRI,”IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 42, No. 4, pp. 880-893, 2018. 미소장
15 C.Y. Wee, P.T. Yap, W. Li, K. Denny, J.N. Browndyke, G.G. Potter et al., “Enriched White Matter Connectivity Networks for Accurate Identification of MCI　Aatients,” Neuroimage, Vol. 54, No. 3, pp. 1812-1822, 2011. 미소장
16 F. Barkhof, T.M. Polvikoski, E.C.W. Van Straaten, R.N. Kalaria, R. Sulkava, H.J. Aronen et al., “The Significance of Medial Temporal Lobe Atrophy: a Postmortem MRI Study in the Very Old,” Neurology, Vol. 69, No. 15, pp. 1521-1527, 2007. 미소장
17 K.I. Diamantaras, and S.Y. Kung, “Principal Component Neural Networks: Ttheory and Applications,” John Wiley & Sons, Inc., 1996. 미소장
18 J. Barnes, J.W. Bartlett, L.A. van de Pol, C.T. Loy, R.I. Scahill, C. Frost et al., “A Meta-Analysis of Hippocampal Atrophy Rates in Alzheimer's Disease,” Neurobiology of Aging, Vol. 30, No. 11, pp. 1711-1723, 2009. 미소장
19 Y. Gupta, K.H. Lee, K.Y. Choi, J.J. Lee, B.C. Kim, and G.R. Kwon, “Alzheimer’s Disease Diagnosis Based on Cortical and Subcortical Features,” Journal of Healthcare Engineering, Vol. 2019, Article ID 2492719, 2019. 미소장
20 R.K. Lama, J. Gwak, J.S. Park, and S.W. Lee, “Diagnosis of Alzheimer’s Disease Based on Structural MRI Images Using a Regularized Extreme Learning Machine and PCA Features,”Journal of Healthcare Engineering, Vol. 2017, PMID 29065619, 2017. 미소장
21 D. Jha, S. Alam, J.Y. Pyun, K.H. Lee, and G.-R. Kwon, “Alzheimer’s Disease Detection Using Extreme Learning Machine, Complex Dual Tree Wavelet Principal Coefficients and Linear Discriminant Dnalysis,” Journal of Medical Imaging and Health Informatics, Vol. 8, No. 5, pp. 881-890, 2018. 미소장
22 S.H. Nozadi, S. Kadoury, and The Alzheimer’s Disease Neuroimaging Initiative, “Classification of Alzheimer’s and MCI Patients from Semantically Parcelled PET Images: a Comparison between AV45 and FDG-PET,”International Journal of Biomedical Imaging, Vol. 2018, Article ID 12417430, 2018. 미소장
23 M. Khajehnejad, F. Saatlou, and H. Mohammadzade, “Alzheimer’s Disease Early Diagnosis Using Manifold-Based Semi- Supervised Learning,” Brain Sciences, Vol. 7, No. 12, pp. 1-19, 2017. 미소장
24 J. Islam and Y. Zhang, “An Ensemble of Deep Convolutional Neural Networks for Alzheimer’s Disease Detection and Classification,” arXiv preprint, arXiv:171201675v2, Dec. 2017. 미소장
25 R. Wolz, V. Julkunen, J. Koikkalainen, E. Niskanen, D.P. Zhang, D. Rueckert et al., “Multi-Method Analysis of MRI Images in Early Diagnostics of Alzheimer's Disease,”PloS One, Vol. 6, No. 10, e25446, 2011. 미소장

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