Browse > Article

SNU Videome Project: 인간수준의 비디오 학습 기술  

Jang, Byeong-Tak (서울대학교)
Keywords
Citations & Related Records
Times Cited By KSCI : 2  (Citation Analysis)
연도 인용수 순위
1 Chater, N. & Manning, C. D., Probabilistic models of language processing and acquisition, Trends in Cognitive Sciences, 10(7): 335-344, 2006.   DOI   ScienceOn
2 Fareed, U. & Zhang, B.-T., MMG: A learning game platform for understanding and predicting human recall memory, Lecture Notes in Artificial Intelligence: PKAW- 2010, 6232: 300-309, 2010.
3 Ha, J.-W., Kim, B.-H., Lee, B., & Zhang, B.-T., Layered hypernetwork models for cross-modal associative text and image keyword generation in multimodal information retrieval, Lecture Notes in Artificial Intelligence: PRICAI-2010, 6230:76-87, 2010.
4 Smith, L.B. & Yu, C., Infants rapidly learn word-referent mappings via cross-situational statistics, Cognition, 106: 333-338, 2008.
5 Thrun, S., A personal account of the development of Stanley, the robot that won the DARPA Grand Challenge, AI Magazine, 27(4): 69-82, 2006.
6 Bishop, C., Pattern Recognition and Machine Learning, Springer, 2006.
7 Duda, R. O., Hart, P. E., & Stork, D. G., Pattern Classification, Wiley, 2000.
8 장병탁, 차세대 기계학습 기술, 정보과학회지, 제25 권, 제3호, pp. 96-107, 2007년 3월.
9 Michalski, R. S., Carbonell, J. G., & Mitchell, T. M. (Eds.), Machine Learning: An Artificial Intelligence Approach, Springer, 1984.
10 Rumelhart, D. E. & McClleland, J. L. (Eds.) Parallel Distributed Processing, Vol. I, MIT Press, 1987.
11 Aarts, E. & Korst, J., Simulated Annealing and Boltzmann Machines: A Stochastic Approach to Combinatorial Optimization and Neural Computing, Wiley, 1989.
12 Neal, R. M., Probabilistic Inference Using Markov Chain Monte Carlo Methods, Technical Report CRGTR- 93-1, Dept. of Computer Science, University of Toronto, 1993.
13 Jordan, M. I., Learning in Graphical Models, MIT Press, 1998.
14 Luck, S. J. & Hollingworth, A. (Eds.), Visual Memory, Oxford University Press, 2008.
15 Frank, M. C., Slemmer, J. A., Marcus, G., & Johnson, S. P., Information from multiple modalities helps fivemonth- olds learn abstract rules, Developmental Science, 12: 504-509, 2009.   DOI   ScienceOn
16 이지훈, 이은석, 장병탁, 유아 언어학습에 대한 하이퍼망 메모리 기반 모델, 정보과학회논문지: 컴퓨팅의 실제 및 레터, 제15권 제12호), 983-987, 2009.
17 Heo, M.-O., Kang, M.-G., & Zhang, B.-T., Visual query expansion via incremental hypernetwork models of image and text, Lecture Notes in Artificial Intelligence: PRICAI-2010, 6230: 88-99, 2010.
18 장병탁, 나노바이오지능분자컴퓨터: 컴퓨터공학과 바이오공학, 나노기술, 인지뇌과학의 만남, 정보과학회지, 제23권 제5호 pp. 41-56, 2005년 5월.
19 Sendhoff, B., Koerner, E., Sporns, O., Ritter, H., & Doya, K., Creating Brain-Like Intelligence, Springer, 2009.
20 Doya, K., Ishii, S., Pouget, A., & Rao, R. (Eds.), Bayesian Brain: Probabilistic Approaches to Neural Coding, MIT Press, 2007.
21 Chater, N. & Oaksford, M. (Eds.), The Probabilistic Mind: Prospects for Bayesian Cognitive Science, Oxford University Press, 2008.
22 Griffiths, T. L., Chater, N., Kemp, C., Perfors, A., & Tenenbaum, J. B., Probabilistic models of cognition: Exploring representations and inductive biases, Trends in Cognitive Sciences, 14: 357-364, 2010.
23 Eichenbaum, H., Learning & Memory, Norton, 2008.
24 Spivey, M., The Continuity of Mind, Oxford University Press, 2008.
25 Lefrancois, G. R., Theories of Human Learning, Thomson, 2006.
26 van Campen, C., The Hidden Sense: Synesthesia in Art and Science, MIT Press, 2007.
27 Turing, A. M., Computing machinery and intelligence, Mind, 59: 433-460, 1950.
28 Cassimatis, N. L., Mueller, E. K., & Winston, P. H., Achieving human-level intelligence through integrated systems and research: introduction to this special issue, AI Magazine, 27(2): 12-14, 2006.
29 Langley, P., Cognitive architectures and general intelligent systems, AI Magazine, 27(2): 33-44, 2006.
30 Squire, L. R. & Kandel, E. R., Memory: From Mind to Molecules, Roberts & Company, 2009.
31 Turner, M. & Fauconnier, G., The Way We Think. Conceptual Blending and the Mind's Hidden Complexities, Basic Books, 2002.
32 Schonfeld, D., Shan, C., Tao, D., & Wang, L., Video Search and Mining, Springer, 2010.
33 Zheng, N. & Xue, J. Statistical Learning and Pattern Analysis for Image and Video Processing, Springer, 2009.
34 Yuille, A. & Kersten, D., Vision as Bayesian inference: analysis by synthesis?, Trends in Cognitive Sciences, 10(7): 301-308, 2006.   DOI   ScienceOn
35 Schoelkopf, B. and Smola, A., Learning with Kernels: Support Vector Machines, Regularization, Optimization,and Beyond, MIT Press, 2001.
36 MacKay, D. J. C., Information Theory, Inference, and Learning Algorithms, Cambridge University Press, 2003.
37 Koller, D. & Friedman, N., Probabilistic Graphical Models: Principles and Techniques, MIT Press, 2009.
38 Hjort, N. L., Holmes, C., Müller, P., & Walker, S. G. (Eds.), Bayesian Nonparametrics, Cambridge University Press, 2010.
39 Zhang, B.-T., Dynamic Learning: Architectures and Algorithms, Graduate Course Notes, School of Computer Science and Engineering, Seoul National University, http://bi.snu.ac.kr/Courses/g-ai10f/g-dl10f.html, 2010.
40 Minsky, M., The Emotion Machine: Commonsense Thinking, Artificial Intelligence, and the Future of the Human Mind, Simon & Schuster, 2007.
41 Rumelhart, D. E., Brain style computation: learning and generalization, In: An Introduction to Neural and Electronic Networks, Academic Press, 1990.
42 Hinton, G. E. & Salakhutdinov, R. R., Reducing the dimensionality of data with neural networks, Science, 313(5786): 504-507, 2006.   DOI   ScienceOn
43 Rudy, J. W., The Neurobiology of Learning and Memory, Sinauer, 2008.
44 van Hemmen, J. L. & Sejnowski, T. J., 23 Problems in Systems Neuroscience, Oxford University Press, 2006.
45 Bear, M. F., Connors, B. W., & Paradiso, M. A., Neuroscience: Exploring the Brain, Lippincott Williams & Wilkins, 2007.
46 Pomerantz, J. R., Topics in Integrative Neuroscience, Cambridge University Press, 2008.
47 Gazzaniga, M. S., Ivry, R. B., & Mangun, G. R., Cognitive Neuroscience: The Biology of the Mind, Norton, 2008.
48 Sporns, O., Networks in the Brain, MIT Press, 2010.
49 McCarthy, J., From here to human-level AI, Artificial Intelligence, 171: 1174-1182, 2007.   DOI   ScienceOn
50 McClelland, J. L., Is a machine realization of truly human-like intelligence achievable?, Cognitive Computation, 1(1): 4-16, 2009.   DOI   ScienceOn
51 Zhang, B.-T., Hypernetworks: A molecular evolutionary architecture for cognitive learning and memory, IEEE Computational Intelligence Magazine, 3(3): 49-63, 2008.
52 Zhang, B.-T., Cognitive learning and the multimodal memory game: Toward human-level machine learning, IEEE World Congress on Computational Intelligence (WCCI-2008), pp. 3261-3267.
53 Zhang, B.-T., Teaching an agent by playing a multimodal memory game: challenges for machine learners and human teachers, AAAI 2009 Spring Symposium: Agents that Learn from Human Teachers, pp. 144-149, 2009.