메뉴 건너뛰기




Volumn , Issue , 2017, Pages 133-141

DeepHash for image instance retrieval: Getting regularization, depth and fine-tuning right

Author keywords

CNN; Fisher vectors; Hashing; Image instance retrieval; RBM; Regularization; Siamese network

Indexed keywords

NEURAL NETWORKS;

EID: 85021783306     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/3078971.3078983     Document Type: Conference Paper
Times cited : (22)

References (51)
  • 14
    • 0019574599 scopus 로고
    • Random sample consensus: A paradigm for model fitting with applications to image analysis and automated cartography
    • June
    • M. A. Fischler and R. C. Bolles. Random Sample Consensus: A Paradigm for Model Fitting with Applications to Image Analysis and Automated Cartography. Communications of ACM, 24(6):381-395, June 1981.
    • (1981) Communications of ACM , vol.24 , Issue.6 , pp. 381-395
    • Fischler, M.A.1    Bolles, R.C.2
  • 16
    • 84887391600 scopus 로고    scopus 로고
    • Learning binary codes for high-dimensional data using bilinear projections
    • Yunchao Gong, Sanjiv Kumar, Henry Rowley, and Svetlana Lazebnik. Learning Binary Codes for High-Dimensional Data Using Bilinear Projections. In Proceedings of CVPR, pages 484-491, 2013.
    • (2013) Proceedings of CVPR , pp. 484-491
    • Gong, Y.1    Kumar, S.2    Rowley, H.3    Lazebnik, S.4
  • 18
    • 84867496527 scopus 로고    scopus 로고
    • Learning binary hash codes for large-scale image search
    • Kristen Grauman and Rob Fergus. Learning Binary Hash Codes for Large-Scale Image Search. In Machine Learning for Computer Vision, volume 411, pages 49-87. 2013.
    • (2013) Machine Learning for Computer Vision , vol.411 , pp. 49-87
    • Grauman, K.1    Fergus, R.2
  • 20
    • 84872506495 scopus 로고    scopus 로고
    • A practical guide to training restricted boltzmann machines
    • Springer Berlin Heidelberg
    • Geoffrey Hinton. A Practical Guide to Training Restricted Boltzmann Machines. In Neural Networks: Tricks of the Trade, volume 7700 of LNCS, pages 599-619. Springer Berlin Heidelberg, 2012.
    • (2012) Neural Networks: Tricks of the Trade, Volume 7700 of LNCS , pp. 599-619
    • Hinton, G.1
  • 21
    • 0013344078 scopus 로고    scopus 로고
    • Training products of experts by minimizing contrastive divergence
    • Geoffrey E Hinton. Training products of experts by minimizing contrastive divergence. Neural Computation, 14(8):1771-1800, 2002.
    • (2002) Neural Computation , vol.14 , Issue.8 , pp. 1771-1800
    • Hinton, G.E.1
  • 22
    • 33745805403 scopus 로고    scopus 로고
    • A fast learning algorithm for deep belief networks
    • Geoffrey E. Hinton, Simon Osindero, and Yee-Whye Teh. A fast learning algorithm for deep belief networks. Neural Computation, 18(7):1527-1554, 2006.
    • (2006) Neural Computation , vol.18 , Issue.7 , pp. 1527-1554
    • Hinton, G.E.1    Osindero, S.2    Teh, Y.-W.3
  • 23
    • 56749104169 scopus 로고    scopus 로고
    • Hamming embedding and weak geometric consistency for large scale image search
    • Berlin, Heidelberg, October
    • H. Jégou, M. Douze, and C. Schmid. Hamming Embedding and Weak Geometric Consistency for Large Scale Image Search. In Proceedings of European Conference on Computer Vision (ECCV), pages 304-317, Berlin, Heidelberg, October 2008.
    • (2008) Proceedings of European Conference on Computer Vision (ECCV) , pp. 304-317
    • Jégou, H.1    Douze, M.2    Schmid, C.3
  • 31
    • 84897560109 scopus 로고    scopus 로고
    • Learning hash functions using column generation
    • Xi Li, Guosheng Lin, Chunhua Shen, Anton van den Hengel, and Anthony R. Dick. Learning Hash Functions Using Column Generation. In Proceedings of ICML, volume 28, pages 142-150, 2013.
    • (2013) Proceedings of ICML , vol.28 , pp. 142-150
    • Li, X.1    Lin, G.2    Shen, C.3    Van den Hengel, A.4    Dick, A.R.5
  • 35
    • 3042535216 scopus 로고    scopus 로고
    • Distinctive image features from scale-invariant keypoints
    • November
    • D. Lowe. Distinctive Image Features from Scale-invariant Keypoints. International Journal of Computer Vision, 60(2):91-110, November 2004.
    • (2004) International Journal of Computer Vision , vol.60 , Issue.2 , pp. 91-110
    • Lowe, D.1
  • 39
    • 80053457714 scopus 로고    scopus 로고
    • Minimal loss hashing for compact binary codes
    • Mohammad Norouzi and David Fleet. Minimal Loss Hashing for Compact Binary Codes. In Proceedings of ICML, pages 353-360, 2011.
    • (2011) Proceedings of ICML , pp. 353-360
    • Norouzi, M.1    Fleet, D.2
  • 41
    • 34948903793 scopus 로고    scopus 로고
    • Object retrieval with large vocabularies and fast spatial matching
    • Minneapolis, Minnesota, June
    • J. Philbin, O. Chum, M. Isard, J. Sivic, and A. Zisserman. Object Retrieval with Large Vocabularies and Fast Spatial Matching. In Proceedings of CVPR, pages 1-8, Minneapolis, Minnesota, June 2007.
    • (2007) Proceedings of CVPR , pp. 1-8
    • Philbin, J.1    Chum, O.2    Isard, M.3    Sivic, J.4    Zisserman, A.5
  • 43
    • 84933585162 scopus 로고    scopus 로고
    • Very deep convolutional networks for large-scale image recognition
    • abs/1409.1556
    • Karen Simonyan and Andrew Zisserman. Very deep convolutional networks for large-scale image recognition. CoRR, abs/1409.1556, 2014.
    • (2014) CoRR
    • Simonyan, K.1    Zisserman, A.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.