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Volumn 2016-December, Issue , 2016, Pages 2138-2146

Dictionary Pair Classifier Driven Convolutional Neural Networks for Object Detection

Author keywords

[No Author keywords available]

Indexed keywords

CLASSIFIERS; COMPLEX NETWORKS; COMPUTER VISION; CONVOLUTION; FEATURE EXTRACTION; LEARNING ALGORITHMS; NEURAL NETWORKS; OBJECT RECOGNITION; PATTERN RECOGNITION;

EID: 84986327418     PISSN: 10636919     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CVPR.2016.235     Document Type: Conference Paper
Times cited : (49)

References (39)
  • 1
    • 84973389608 scopus 로고    scopus 로고
    • Analyzing the performance of multilayer neural networks for object recognition
    • P. Agrawal, R. Girshick, and J. Malik. Analyzing the performance of multilayer neural networks for object recognition. In ECCV, 2014.
    • (2014) ECCV
    • Agrawal, P.1    Girshick, R.2    Malik, J.3
  • 2
    • 84887369873 scopus 로고    scopus 로고
    • Measuring the objectness of image windows
    • B. Alexe, T. Deselaers, and V. Ferrari. Measuring the objectness of image windows. TPAMI, 2010.
    • (2010) TPAMI
    • Alexe, B.1    Deselaers, T.2    Ferrari, V.3
  • 4
    • 0031189914 scopus 로고    scopus 로고
    • Multitask learning
    • R. Caruana. Multitask learning. Machine learning, 28:41-75, 1997.
    • (1997) Machine Learning , vol.28 , pp. 41-75
    • Caruana, R.1
  • 6
    • 84911443425 scopus 로고    scopus 로고
    • Scalable object detection using deep neural networks
    • June
    • D. Erhan, C. Szegedy, A. Toshev, and D. Anguelov. Scalable object detection using deep neural networks. In CVPR, June 2014.
    • (2014) CVPR
    • Erhan, D.1    Szegedy, C.2    Toshev, A.3    Anguelov, D.4
  • 9
    • 84875713469 scopus 로고    scopus 로고
    • Joint discriminative dimensionality reduction and dictionary learning for face recognition
    • Z. Feng, M. Yang, L. Zhang, Y. Liu, and D. Zhang. Joint discriminative dimensionality reduction and dictionary learning for face recognition. Pattern Recognition, 46:2134-2143, 2013.
    • (2013) Pattern Recognition , vol.46 , pp. 2134-2143
    • Feng, Z.1    Yang, M.2    Zhang, L.3    Liu, Y.4    Zhang, D.5
  • 10
    • 84891772600 scopus 로고    scopus 로고
    • Learning category-specific dictionary and shared dictionary for fine-grained image categorization
    • Feb
    • S. Gao, I.-H. Tsang, and Y. Ma. Learning category-specific dictionary and shared dictionary for fine-grained image categorization. Image Processing, IEEE Transactions on, 23(2):623-634, Feb 2014.
    • (2014) Image Processing, IEEE Transactions on , vol.23 , Issue.2 , pp. 623-634
    • Gao, S.1    Tsang, I.-H.2    Ma, Y.3
  • 11
    • 84973864191 scopus 로고    scopus 로고
    • Object detection via a multiregion & semantic segmentation-aware cnn model
    • S. Gidaris and N. Komodakis. Object detection via a multiregion & semantic segmentation-aware cnn model. In ICCV, 2015.
    • (2015) ICCV
    • Gidaris, S.1    Komodakis, N.2
  • 12
    • 85029359197 scopus 로고    scopus 로고
    • Fast r-cnn
    • R. Girshick. Fast r-cnn. In ICCV, 2015.
    • (2015) ICCV
    • Girshick, R.1
  • 13
    • 84911400494 scopus 로고    scopus 로고
    • Rich feature hierarchies for accurate object detection and semantic segmentation
    • R. Girshick, J. Donahue, T. Darrell, and J. Malik. Rich feature hierarchies for accurate object detection and semantic segmentation. In CVPR, 2014.
    • (2014) CVPR
    • Girshick, R.1    Donahue, J.2    Darrell, T.3    Malik, J.4
  • 14
    • 84959195179 scopus 로고    scopus 로고
    • Deformable part models are convolutional neural networks
    • R. Girshick, F. Iandola, T. Darrell, and J. Malik. Deformable part models are convolutional neural networks. In CVPR, 2015.
    • (2015) CVPR
    • Girshick, R.1    Iandola, F.2    Darrell, T.3    Malik, J.4
  • 16
    • 84939247735 scopus 로고    scopus 로고
    • Spatial pyramid pooling in deep convolutional networks for visual recognition
    • K. He, X. Zhang, S. Ren, and J. Sun. Spatial pyramid pooling in deep convolutional networks for visual recognition. TPAMI, 2015.
    • (2015) TPAMI
    • He, K.1    Zhang, X.2    Ren, S.3    Sun, J.4
  • 18
    • 84884571014 scopus 로고    scopus 로고
    • Label consistent k-SVD: Learning a discriminative dictionary for recognition
    • Z. Jiang, Z. Lin, and L. Davis. Label consistent k-svd: learning a discriminative dictionary for recognition. TPAMI, 34, 2013.
    • (2013) TPAMI , vol.34
    • Jiang, Z.1    Lin, Z.2    Davis, L.3
  • 21
    • 80052726060 scopus 로고    scopus 로고
    • Representing and recognizing objects with massive local image patches
    • L. Lin, P. Luo, X. Chen, and K. Zeng. Representing and recognizing objects with massive local image patches. Pattern Recognition, 45:231-240, 2012.
    • (2012) Pattern Recognition , vol.45 , pp. 231-240
    • Lin, L.1    Luo, P.2    Chen, X.3    Zeng, K.4
  • 22
    • 84857419890 scopus 로고    scopus 로고
    • Task-driven dictionary learning
    • J. Mairal, F. Bach, and J. Ponce. Task-driven dictionary learning. TPAMI, 35, 2012.
    • (2012) TPAMI , vol.35
    • Mairal, J.1    Bach, F.2    Ponce, J.3
  • 23
    • 77955994663 scopus 로고    scopus 로고
    • Classification and clustering via dictionary learning with structured incoherence and shared features
    • I. Ramirez, P. Sprechmann, and G. Sapiro. Classification and clustering via dictionary learning with structured incoherence and shared features. In CVPR, 2010.
    • (2010) CVPR
    • Ramirez, I.1    Sprechmann, P.2    Sapiro, G.3
  • 24
    • 84960980241 scopus 로고    scopus 로고
    • Faster r-cnn: Towards real-time object detection with region proposal networks
    • S. Ren, K. He, R. Girshick, and J. Sun. Faster r-cnn: Towards real-time object detection with region proposal networks. In NIPS, 2015.
    • (2015) NIPS
    • Ren, S.1    He, K.2    Girshick, R.3    Sun, J.4
  • 26
    • 85083951635 scopus 로고    scopus 로고
    • Overfeat: Integrated recognition, localization and detection using convolutional networks
    • P. Sermanet, D. Eigen, X. Zhang, M. Mathieu, R. Fergus, and Y. LeCun. Overfeat: Integrated recognition, localization and detection using convolutional networks. In ICLR 2014, April 2014.
    • (2014) ICLR , pp. April
    • Sermanet, P.1    Eigen, D.2    Zhang, X.3    Mathieu, M.4    Fergus, R.5    LeCun, Y.6
  • 27
    • 85083953063 scopus 로고    scopus 로고
    • Very deep convolutional networks for large-scale image recognition
    • K. Simonyan and A. Zisserman. Very deep convolutional networks for large-scale image recognition. In ICLR, 2015.
    • (2015) ICLR
    • Simonyan, K.1    Zisserman, A.2
  • 32
    • 84959203164 scopus 로고    scopus 로고
    • End-to-end integration of a convolution network, deformable parts model and nonmaximum suppression
    • L. Wan, D. Eigen, and R. Fergus. End-to-end integration of a convolution network, deformable parts model and nonmaximum suppression. In CVPR, 2015.
    • (2015) CVPR
    • Wan, L.1    Eigen, D.2    Fergus, R.3
  • 33
    • 84887381206 scopus 로고    scopus 로고
    • Incorporating structural alternatives and sharing into hierarchy for multiclass object recognition and detection
    • X. Wang, L. Lin, L. Huang, and S. Yan. Incorporating structural alternatives and sharing into hierarchy for multiclass object recognition and detection. In CVPR, 2013.
    • (2013) CVPR
    • Wang, X.1    Lin, L.2    Huang, L.3    Yan, S.4
  • 34
    • 84898769710 scopus 로고    scopus 로고
    • Regionlets for generic object detection
    • X.Wang, M. Yang, S. Zhu, and Y. Lin. Regionlets for generic object detection. In ICCV, 2013.
    • (2013) ICCV
    • Wang, X.1    Yang, M.2    Zhu, S.3    Lin, Y.4
  • 36
    • 84905671639 scopus 로고    scopus 로고
    • Sparse representation based fisher discrimination dictionary learning for image classification
    • M. Yang, L. Zhang, X. Feng, and D. Zhang. Sparse representation based fisher discrimination dictionary learning for image classification. IJCV, 109, 2014.
    • (2014) IJCV , vol.109
    • Yang, M.1    Zhang, L.2    Feng, X.3    Zhang, D.4
  • 37
    • 84863011302 scopus 로고    scopus 로고
    • Sparse representation or collaborative representation: Which helps face recognition?
    • L. Zhang, M. Yang, and X. Feng. Sparse representation or collaborative representation: Which helps face recognition? In ICCV, 2011.
    • (2011) ICCV
    • Zhang, L.1    Yang, M.2    Feng, X.3
  • 38
    • 84959196836 scopus 로고    scopus 로고
    • Improving object detection with deep convolutional networks via Bayesian optimization and structured prediction
    • Y. Zhang, K. Sohn, R. Villegas, G. Pan, and H. Lee. Improving object detection with deep convolutional networks via Bayesian optimization and structured prediction. In CVPR, 2015.
    • (2015) CVPR
    • Zhang, Y.1    Sohn, K.2    Villegas, R.3    Pan, G.4    Lee, H.5
  • 39
    • 84959233955 scopus 로고    scopus 로고
    • Segdeepm: Exploiting segmentation and context in deep neural networks for object detection
    • June
    • Y. Zhu, R. Urtasun, R. Salakhutdinov, and S. Fidler. segdeepm: Exploiting segmentation and context in deep neural networks for object detection. In CVPR, June 2015.
    • (2015) CVPR
    • Zhu, Y.1    Urtasun, R.2    Salakhutdinov, R.3    Fidler, S.4


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.