메뉴 건너뛰기




Volumn 3, Issue , 2005, Pages 1229-1234

Sensor selection for active information fusion

Author keywords

[No Author keywords available]

Indexed keywords

GRAPH-THEORETIC APPROACH; INFORMATION GATHERING; SENSOR SELECTION; SUBSETS;

EID: 29344436763     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (8)

References (18)
  • 3
    • 32944472224 scopus 로고    scopus 로고
    • Representting uncertainties using bayesian networks
    • DSTO Electronics and Surveillance Research Laboratory, Salisbury South Australia 5108, Australia
    • Das, B. 1999. Representting uncertainties using bayesian networks. Technical Report DSTO-TR-0918, DSTO Electronics and Surveillance Research Laboratory, Salisbury South Australia 5108, Australia.
    • (1999) Technical Report , vol.DSTO-TR-0918
    • Das, B.1
  • 4
    • 0036473286 scopus 로고    scopus 로고
    • Information theoretic sensor data selection for active object recognition and state estimation
    • Denzler, J., and Brown, C. M. 2002. Information theoretic sensor data selection for active object recognition and state estimation. IEEE Trans. Pattern Anal. Machine Intell. 24(2):145-157.
    • (2002) IEEE Trans. Pattern Anal. Machine Intell. , vol.24 , Issue.2 , pp. 145-157
    • Denzler, J.1    Brown, C.M.2
  • 5
    • 3042705008 scopus 로고    scopus 로고
    • Maximum mutual information principle for dynamic sensor query
    • Ertin, E.; Fisher, J.; and Potter, L. 2003. Maximum mutual information principle for dynamic sensor query. In Proc. IPSN'03.
    • (2003) Proc. IPSN'03
    • Ertin, E.1    Fisher, J.2    Potter, L.3
  • 6
    • 0346639284 scopus 로고    scopus 로고
    • A new probabilistic and entropy fusion approach for management of information sources
    • Fassinut-Mombot, B., and Choquel, J.-B. 2004. A new probabilistic and entropy fusion approach for management of information sources. Information Fusion 5:35-47.
    • (2004) Information Fusion , vol.5 , pp. 35-47
    • Fassinut-Mombot, B.1    Choquel, J.-B.2
  • 7
    • 0027556865 scopus 로고
    • An approximate nonmyopic computation for value of information
    • Heckerman, D.; Horvitz, E.; and Middleton, B. 1993. An approximate nonmyopic computation for value of information. IEEE Trans. on PAMI 15(3):292-298.
    • (1993) IEEE Trans. on PAMI , vol.15 , Issue.3 , pp. 292-298
    • Heckerman, D.1    Horvitz, E.2    Middleton, B.3
  • 10
    • 0036611772 scopus 로고    scopus 로고
    • Algorithms for optimal scheduling and management of Hidden Markov Model sensors
    • Krishnamurthy, V. 2002. Algorithms for optimal scheduling and management of Hidden Markov Model sensors. IEEE Trans. on Signal Processing 50(6):1382-1397.
    • (2002) IEEE Trans. on Signal Processing , vol.50 , Issue.6 , pp. 1382-1397
    • Krishnamurthy, V.1
  • 11
    • 0031100492 scopus 로고    scopus 로고
    • Sensor planning with bayesian decision theory
    • Kristensen, S. 1997. Sensor planning with bayesian decision theory. Robotics and Autonomous Systems 19(3):273-286.
    • (1997) Robotics and Autonomous Systems , vol.19 , Issue.3 , pp. 273-286
    • Kristensen, S.1
  • 13
  • 14
    • 0031140438 scopus 로고    scopus 로고
    • Optimization of observations: A stochastic control approach
    • Miller, B. M., and Runggaldier, W. J. 1997. Optimization of observations: a stochastic control approach. SIAM J. Control Optimal 35(5):1030-1052.
    • (1997) SIAM J. Control Optimal , vol.35 , Issue.5 , pp. 1030-1052
    • Miller, B.M.1    Runggaldier, W.J.2
  • 15
    • 29344467440 scopus 로고    scopus 로고
    • Selective perception policies for guiding sensing and computation in multimodal systems: A comparative analysis
    • Oliver, N., and Horvitz, E. 2003. Selective perception policies for guiding sensing and computation in multimodal systems: A comparative analysis. In Proc. the 5th ICML.
    • (2003) Proc. the 5th ICML
    • Oliver, N.1    Horvitz, E.2
  • 16
    • 0033741106 scopus 로고    scopus 로고
    • Active object recognition by view integration and reinforcement learning
    • Paletta, L., and Pinz, A. 2000. Active object recognition by view integration and reinforcement learning. Robotics and Autonomous System (31):71-86.
    • (2000) Robotics and Autonomous System , Issue.31 , pp. 71-86
    • Paletta, L.1    Pinz, A.2
  • 18
    • 85032751029 scopus 로고    scopus 로고
    • Information-driven dynamic sensor collaboration for tracking application
    • Zhao, F.; Shin, J.; and Reich, J. 2002. Information-driven dynamic sensor collaboration for tracking application. IEEE Signal Processing Magazine 19(1):61-72.
    • (2002) IEEE Signal Processing Magazine , vol.19 , Issue.1 , pp. 61-72
    • Zhao, F.1    Shin, J.2    Reich, J.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.