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Volumn 9906 LNCS, Issue , 2016, Pages 660-676

Learning to count with CNN boosting

Author keywords

Convolutional neural networks; Counting; Gradient boosting; Sample selection

Indexed keywords

IMAGE SEGMENTATION; NEURAL NETWORKS;

EID: 84990864917     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-319-46475-6_41     Document Type: Conference Paper
Times cited : (322)

References (38)
  • 1
    • 85162384490 scopus 로고    scopus 로고
    • Learning to count objects in images
    • Lafferty, J.D., Williams, C.K.I., Shawe-Taylor, J., Zemel, R.S., Culotta, A. (eds.), Curran Associates Inc
    • Lempitsky, V., Zisserman, A.: Learning to count objects in images. In: Lafferty, J.D., Williams, C.K.I., Shawe-Taylor, J., Zemel, R.S., Culotta, A. (eds.) Advances in Neural Information Processing Systems 23, pp. 1324-1332. Curran Associates Inc. (2010)
    • (2010) Advances in Neural Information Processing Systems 23 , pp. 1324-1332
    • Lempitsky, V.1    Zisserman, A.2
  • 3
    • 51949104316 scopus 로고    scopus 로고
    • Privacy preserving crowd monitoring: Counting people without people models or tracking
    • Chan, A.B., sheng John, Z., Vasconcelos, L.N.: Privacy preserving crowd monitoring:counting people without people models or tracking. In: CVPR, pp. 1-7 (2008)
    • (2008) CVPR , pp. 1-7
    • Chan, A.B.1    Sheng John, Z.2    Vasconcelos, L.N.3
  • 11
    • 84906495301 scopus 로고    scopus 로고
    • Deep learning of scene-specific classifier for pedestrian detection
    • Fleet, D., Pajdla, T., Schiele, B., Tuytelaars, T. (eds.), Springer, Heidelberg
    • Zeng, X., Ouyang, W., Wang, M., Wang, X.: Deep learning of scene-specific classifier for pedestrian detection. In: Fleet, D., Pajdla, T., Schiele, B., Tuytelaars, T. (eds.) ECCV 2014, Part III. LNCS, vol. 8691, pp. 472-487. Springer, Heidelberg (2014)
    • (2014) ECCV 2014, Part III. LNCS , vol.8691 , pp. 472-487
    • Zeng, X.1    Ouyang, W.2    Wang, M.3    Wang, X.4
  • 18
    • 84990862830 scopus 로고    scopus 로고
    • Improving quality of training samples through exhaustless generation and effective selection for deep convolutional neural networks
    • Yamashita, T., Watasue, T., Yamauchi, Y., Fujiyoshi, H.: Improving quality of training samples through exhaustless generation and effective selection for deep convolutional neural networks. In: ICPR 2012 (2012)
    • (2012) ICPR 2012
    • Yamashita, T.1    Watasue, T.2    Yamauchi, Y.3    Fujiyoshi, H.4
  • 21
    • 0031648023 scopus 로고    scopus 로고
    • Example-based learning for view-based human face detection
    • Sung, K.K., Poggio, T.: Example-based learning for view-based human face detection. IEEE Trans. Pattern Anal. Mach. Intell. 20(1), 39-51 (1998)
    • (1998) IEEE Trans. Pattern Anal. Mach. Intell. , vol.20 , Issue.1 , pp. 39-51
    • Sung, K.K.1    Poggio, T.2
  • 25
  • 27
    • 0035470889 scopus 로고    scopus 로고
    • Greedy function approximation: A gradient boosting machine
    • Friedman, J.H.: Greedy function approximation: A gradient boosting machine. Ann. Stat. 29, 1189-1232 (2000)
    • (2000) Ann. Stat. , vol.29 , pp. 1189-1232
    • Friedman, J.H.1
  • 28
    • 0037186544 scopus 로고    scopus 로고
    • Stochastic gradient boosting
    • Friedman, J.H.: Stochastic gradient boosting. Comput. Stat. Data Anal. 38(4), 367-378 (2002)
    • (2002) Comput. Stat. Data Anal. , vol.38 , Issue.4 , pp. 367-378
    • Friedman, J.H.1
  • 29
    • 83555170269 scopus 로고    scopus 로고
    • Random classification noise defeats all convex potential boosters
    • Long, P.M., Servedio, R.A.: Random classification noise defeats all convex potential boosters. Mach. Learn. 78(3), 287-304 (2009)
    • (2009) Mach. Learn. , vol.78 , Issue.3 , pp. 287-304
    • Long, P.M.1    Servedio, R.A.2
  • 33
    • 77953066727 scopus 로고    scopus 로고
    • Learning depth from single monocular images
    • MIT Press
    • Saxena, A., Chung, S.H., Ng, A.Y.: Learning depth from single monocular images. In: NIPS 18. MIT Press (2005)
    • (2005) NIPS 18
    • Saxena, A.1    Chung, S.H.2    Ng, A.Y.3
  • 34
    • 85162313618 scopus 로고    scopus 로고
    • Towards holistic scene understanding: Feedback enabled cascaded classification models
    • Lafferty, J.D., Williams, C.K.I., Shawe-Taylor, J., Zemel, R.S., Culotta, A. (eds.), Curran Associates Inc
    • Li, C., Kowdle, A., Saxena, A., Chen, T.: Towards holistic scene understanding:feedback enabled cascaded classification models. In: Lafferty, J.D., Williams, C.K.I., Shawe-Taylor, J., Zemel, R.S., Culotta, A. (eds.) Advances in Neural Information Processing Systems 23, pp. 1351-1359. Curran Associates Inc. (2010)
    • (2010) Advances in Neural Information Processing Systems 23 , pp. 1351-1359
    • Li, C.1    Kowdle, A.2    Saxena, A.3    Chen, T.4
  • 35
    • 84867885036 scopus 로고    scopus 로고
    • Depth extraction from video using non-parametric sampling
    • Fitzgibbon, A., Lazebnik, S., Perona, P., Sato, Y., Schmid, C. (eds.), Springer, Heidelberg
    • Karsch, K., Liu, C., Kang, S.B.: Depth extraction from video using non-parametric sampling. In: Fitzgibbon, A., Lazebnik, S., Perona, P., Sato, Y., Schmid, C. (eds.) ECCV 2012, Part V. LNCS, vol. 7576, pp. 775-788. Springer, Heidelberg (2012)
    • (2012) ECCV 2012, Part V. LNCS , vol.7576 , pp. 775-788
    • Karsch, K.1    Liu, C.2    Kang, S.B.3
  • 38
    • 64849095075 scopus 로고    scopus 로고
    • Make3D: Learning 3D scene structure from a single still image
    • Saxena, A., Sun, M., Ng, A.Y.: Make3D: Learning 3D scene structure from a single still image. IEEE Trans. Pattern Anal. Mach. Intell. 31(5), 824-840 (2009)
    • (2009) IEEE Trans. Pattern Anal. Mach. Intell. , vol.31 , Issue.5 , pp. 824-840
    • Saxena, A.1    Sun, M.2    Ng, A.Y.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.