-
1
-
-
3042597440
-
Learning multi-label scene classification
-
M. R. Boutell, J. Luo, X. Shen, and C. M. Brown. Learning multi-label scene classification. Pattern recognition, 37(9):1757-1771, 2004
-
(2004)
Pattern Recognition
, vol.37
, Issue.9
, pp. 1757-1771
-
-
Boutell, M.R.1
Luo, J.2
Shen, X.3
Brown, C.M.4
-
2
-
-
84990032982
-
-
arXiv preprint arXiv:1512.01274
-
T. Chen, M. Li, Y. Li, M. Lin, N. Wang, M. Wang, T. Xiao, B. Xu, C. Zhang, and Z. Zhang. Mxnet: A flexible and efficient machine learning library for heterogeneous distributed systems. ArXiv preprint arXiv:1512.01274, 2015
-
(2015)
Mxnet: A Flexible and Efficient Machine Learning Library for Heterogeneous Distributed Systems
-
-
Chen, T.1
Li, M.2
Li, Y.3
Lin, M.4
Wang, N.5
Wang, M.6
Xiao, T.7
Xu, B.8
Zhang, C.9
Zhang, Z.10
-
3
-
-
85010215432
-
Chalearn looking at people and faces of theworld: Face analysis workshop and challenge 2016, chalearn looking at people and faces of the world
-
S. Escalera, M. Torres, B. Martnez, X. Bar, H. J. Escalante, I. Guyon, G. Tzimiropoulos, C. Corneanu, M. Oliu, M. Ali Bagheri, and M. Valstar. Chalearn looking at people and faces of theworld: Face analysis workshop and challenge 2016, chalearn looking at people and faces of the world. In CVPR workshops, 2016
-
(2016)
CVPR Workshops
-
-
Escalera, S.1
Torres, M.2
Martnez, B.3
Bar, X.4
Escalante, H.J.5
Guyon, I.6
Tzimiropoulos, G.7
Corneanu, C.8
Oliu, M.9
Ali Bagheri, M.10
Valstar, M.11
-
4
-
-
52949105710
-
Multilabel classification via calibrated label ranking
-
J. Fürnkranz, E. Hüllermeier, E. L. Mencá, and K. Brinker. Multilabel classification via calibrated label ranking. Machine learning, 73(2):133-153, 2008
-
(2008)
Machine Learning
, vol.73
, Issue.2
, pp. 133-153
-
-
Fürnkranz, J.1
Hüllermeier, E.2
Mencá, E.L.3
Brinker, K.4
-
7
-
-
84913555165
-
-
arXiv preprint arXiv:1408.5093
-
Y. Jia, E. Shelhamer, J. Donahue, S. Karayev, J. Long, R. Girshick, S. Guadarrama, and T. Darrell. Caffe: Convolutional architecture for fast feature embedding. ArXiv preprint arXiv:1408.5093, 2014
-
(2014)
Caffe: Convolutional Architecture for Fast Feature Embedding
-
-
Jia, Y.1
Shelhamer, E.2
Donahue, J.3
Karayev, S.4
Long, J.5
Girshick, R.6
Guadarrama, S.7
Darrell, T.8
-
8
-
-
84925408679
-
Novel dataset for fine-grained image categorization
-
Colorado Springs, CO, June
-
A. Khosla, N. Jayadevaprakash, B. Yao, and L. Fei-Fei. Novel dataset for fine-grained image categorization. In First Workshop on Fine-Grained Visual Categorization, IEEE Conference on Computer Vision and Pattern Recognition, Colorado Springs, CO, June 2011
-
(2011)
First Workshop on Fine-Grained Visual Categorization, IEEE Conference on Computer Vision and Pattern Recognition
-
-
Khosla, A.1
Jayadevaprakash, N.2
Yao, B.3
Fei-Fei, L.4
-
9
-
-
84992147801
-
-
arXiv preprint arXiv:1511.06789
-
J. Krause, B. Sapp, A. Howard, H. Zhou, A. Toshev, T. Duerig, J. Philbin, and L. Fei-Fei. The unreasonable effectiveness of noisy data for fine-grained recognition. ArXiv preprint arXiv:1511.06789, 2015
-
(2015)
The Unreasonable Effectiveness of Noisy Data for Fine-grained Recognition
-
-
Krause, J.1
Sapp, B.2
Howard, A.3
Zhou, H.4
Toshev, A.5
Duerig, T.6
Philbin, J.7
Fei-Fei, L.8
-
10
-
-
84992143250
-
Learning to recognition from bing clickture data
-
C. Li, Q. Song, Y. Wang, H. Song, Q. Kang, J. Cheng, and H. Lu. Learning to recognition from bing clickture data. MSR Image Recognition Challenge (IRC) @ IEEE ICME, 2016
-
(2016)
MSR Image Recognition Challenge (IRC) @ IEEE ICME
-
-
Li, C.1
Song, Q.2
Wang, Y.3
Song, H.4
Kang, Q.5
Cheng, J.6
Lu, H.7
-
12
-
-
67049088703
-
Multi-label classification using ensembles of pruned sets
-
IEEE
-
J. Read, B. Pfahringer, and G. Holmes. Multi-label classification using ensembles of pruned sets. In Data Mining, 2008. ICDM'08. Eighth IEEE International Conference on, pages 995-1000. IEEE, 2008
-
(2008)
Data Mining, 2008. ICDM'08. Eighth IEEE International Conference on
, pp. 995-1000
-
-
Read, J.1
Pfahringer, B.2
Holmes, G.3
-
13
-
-
83155175374
-
Classifier chains for multi-label classification
-
J. Read, B. Pfahringer, G. Holmes, and E. Frank. Classifier chains for multi-label classification. Machine learning, 85(3):333-359, 2011
-
(2011)
Machine Learning
, vol.85
, Issue.3
, pp. 333-359
-
-
Read, J.1
Pfahringer, B.2
Holmes, G.3
Frank, E.4
-
14
-
-
84960980241
-
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 Advances in Neural Information Processing Systems, pages 91-99, 2015
-
(2015)
Advances in Neural Information Processing Systems
, pp. 91-99
-
-
Ren, S.1
He, K.2
Girshick, R.3
Sun, J.4
-
15
-
-
0033905095
-
Boostexter: A boosting-based system for text categorization
-
R. E. Schapire and Y. Singer. Boostexter: A boosting-based system for text categorization. Machine learning, 39(2):135-168, 2000
-
(2000)
Machine Learning
, vol.39
, Issue.2
, pp. 135-168
-
-
Schapire, R.E.1
Singer, Y.2
-
16
-
-
85083953063
-
Very deep convolutional networks for large-scale image recognition
-
K. Simonyan and A. Zisserman. Very deep convolutional networks for large-scale image recognition. ICLR, 2015
-
(2015)
ICLR
-
-
Simonyan, K.1
Zisserman, A.2
-
17
-
-
84962860806
-
Learning deep features for msr-bing information retrieval challenge
-
ACM
-
Q. Song, S. Yu, C. Leng, J.Wu, Q. Hu, and J. Cheng. Learning deep features for msr-bing information retrieval challenge. In Proceedings of the 23rd Annual ACM Conference on Multimedia Conference, pages 169-172. ACM, 2015
-
(2015)
Proceedings of the 23rd Annual ACM Conference on Multimedia Conference
, pp. 169-172
-
-
Song, Q.1
Yu, S.2
Leng, C.3
Wu, J.4
Hu, Q.5
Cheng, J.6
-
18
-
-
84937522268
-
Going deeper with convolutions
-
June
-
C. Szegedy, W. Liu, Y. Jia, P. Sermanet, S. Reed, D. Anguelov, D. Erhan, V. Vanhoucke, and A. Rabinovich. Going deeper with convolutions. In The IEEE Conference on Computer Vision and Pattern Recognition (CVPR), June 2015
-
(2015)
The IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
-
-
Szegedy, C.1
Liu, W.2
Jia, Y.3
Sermanet, P.4
Reed, S.5
Anguelov, D.6
Erhan, D.7
Vanhoucke, V.8
Rabinovich, A.9
-
19
-
-
84990032289
-
-
arXiv preprint arXiv:1512.00567
-
C. Szegedy, V. Vanhoucke, S. Ioffe, J. Shlens, and Z. Wojna. Rethinking the inception architecture for computer vision. ArXiv preprint arXiv:1512.00567, 2015
-
(2015)
Rethinking the Inception Architecture for Computer Vision
-
-
Szegedy, C.1
Vanhoucke, V.2
Ioffe, S.3
Shlens, J.4
Wojna, Z.5
-
20
-
-
84933515061
-
Multi-label classification: An overview
-
Aristotle University of Thessaloniki, Greece
-
G. Tsoumakas and I. Katakis. Multi-label classification: An overview. Dept. of Informatics, Aristotle University of Thessaloniki, Greece, 2006
-
(2006)
Dept. of Informatics
-
-
Tsoumakas, G.1
Katakis, I.2
-
21
-
-
38049123909
-
Random k-labelsets: An ensemble method for multilabel classification
-
Springer
-
G. Tsoumakas and I. Vlahavas. Random k-labelsets: An ensemble method for multilabel classification. In Machine learning: ECML 2007, pages 406-417. Springer, 2007
-
(2007)
Machine Learning: ECML 2007
, pp. 406-417
-
-
Tsoumakas, G.1
Vlahavas, I.2
-
23
-
-
84878084353
-
-
Technical Report CNS-TR-2011-001, California Institute of Technology
-
C. Wah, S. Branson, P. Welinder, P. Perona, and S. Belongie. The Caltech-UCSD Birds-200-2011 Dataset. Technical Report CNS-TR-2011-001, California Institute of Technology, 2011
-
(2011)
The Caltech-UCSD Birds-200-2011 Dataset
-
-
Wah, C.1
Branson, S.2
Welinder, P.3
Perona, P.4
Belongie, S.5
-
24
-
-
33947681316
-
Ml-knn: A lazy learning approach to multi-label learning
-
M.-L. Zhang and Z.-H. Zhou. Ml-knn: A lazy learning approach to multi-label learning. Pattern recognition, 40(7):2038-2048, 2007.
-
(2007)
Pattern Recognition
, vol.40
, Issue.7
, pp. 2038-2048
-
-
Zhang, M.-L.1
Zhou, Z.-H.2
|