-
1
-
-
84930576933
-
An unsupervised feature learning framework for basal cell carcinoma image analysis
-
Arevalo, J.; Cruz-Roa, A.; Arias, V.; Romero, E.; and Gonzalez, F. A. 2015. An unsupervised feature learning framework for basal cell carcinoma image analysis. Artificial intelligence in medicine.
-
(2015)
Artificial Intelligence in Medicine
-
-
Arevalo, J.1
Cruz-Roa, A.2
Arias, V.3
Romero, E.4
Gonzalez, F.A.5
-
2
-
-
84939543295
-
Automated detection of melanoma in dermoscopic images
-
Scharcanski, J. and Celebi, M. E. eds., Series in BioEngineering. Springer Berlin Heidelberg
-
Arroyo, J., and Zapirain, B. 2014. Automated detection of melanoma in dermoscopic images. In Scharcanski, J., and Celebi, M. E., eds., Computer Vision Techniques for the Diagnosis of Skin Cancer, Series in BioEngineering. Springer Berlin Heidelberg. 139-192.
-
(2014)
Computer Vision Techniques for the Diagnosis of Skin Cancer
, pp. 139-192
-
-
Arroyo, J.1
Zapirain, B.2
-
3
-
-
0031189914
-
Multitask learning
-
Caruana, R. 1997. Multitask learning. Machine Learning 28(1):41-75.
-
(1997)
Machine Learning
, vol.28
, Issue.1
, pp. 41-75
-
-
Caruana, R.1
-
5
-
-
33745355417
-
Diagnosis of skin disease
-
7th edn. Oxford: Blackwell Science
-
Cox, N., and Coulson, I. 2004. Diagnosis of skin disease. Rook's Textbook of Dermatology, 7th edn. Oxford: Blackwell Science 5.
-
(2004)
Rook's Textbook of Dermatology
, pp. 5
-
-
Cox, N.1
Coulson, I.2
-
6
-
-
84901774997
-
Automatic detection of invasive ductal carcinoma in whole slide images with convolutional neural networks
-
904103-904103. International Society for Optics and Photonics
-
Cruz-Roa, A.; Basavanhally, A.; Gonzdlez, F.; Gilmore, H.; Feldman, M.; Ganesan, S.; Shih, N.; Tomaszewski, J.; and Madabhushi, A. 2014. Automatic detection of invasive ductal carcinoma in whole slide images with convolutional neural networks. In SPIE Medical Imaging, 904103-904103. International Society for Optics and Photonics.
-
(2014)
SPIE Medical Imaging
-
-
Cruz-Roa, A.1
Basavanhally, A.2
Gonzdlez, F.3
Gilmore, H.4
Feldman, M.5
Ganesan, S.6
Shih, N.7
Tomaszewski, J.8
Madabhushi, A.9
-
7
-
-
85198028989
-
Imagenet: A large-scale hierarchical image database
-
20-25 June 2009, Miami, Florida, USA
-
Deng, J.; Dong, W.; Socher, R.; Li, L.; Li, K.; and Li, F. 2009. Imagenet: A large-scale hierarchical image database. In 2009 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2009), 20-25 June 2009, Miami, Florida, USA, 248-255.
-
(2009)
2009 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2009)
, pp. 248-255
-
-
Deng, J.1
Dong, W.2
Socher, R.3
Li, L.4
Li, K.5
Li, F.6
-
8
-
-
84919881041
-
Decaf: A deep convolutional activation feature for generic visual recognition
-
ICML 2014, Beijing, China, 21-26 June 2014
-
Donahue, J.; Jia, Y.; Vinyals, O.; Hoffman, J.; Zhang, N.; Tzeng, E.; and Darrell, T. 2014. Decaf: A deep convolutional activation feature for generic visual recognition. In Proceedings of the 31th International Conference on Machine Learning, ICML 2014, Beijing, China, 21-26 June 2014, 647-655.
-
(2014)
Proceedings of the 31th International Conference on Machine Learning
, pp. 647-655
-
-
Donahue, J.1
Jia, Y.2
Vinyals, O.3
Hoffman, J.4
Zhang, N.5
Tzeng, E.6
Darrell, T.7
-
10
-
-
77951298115
-
The pascal visual object classes (VOC) challenge
-
Everingham, M.; Gool, L. J. V.; Williams, C. K. I.; Winn, J. M.; and Zisserman, A. 2010. The pascal visual object classes (VOC) challenge. International Journal of Computer Vision 88(2):303-338.
-
(2010)
International Journal of Computer Vision
, vol.88
, Issue.2
, pp. 303-338
-
-
Everingham, M.1
Gool, L.J.V.2
Williams, C.K.I.3
Winn, J.M.4
Zisserman, A.5
-
11
-
-
84947425172
-
Automatic diagnosis of melanoma based on the 7-point checklist
-
Scharcanski, J. and Celebi, M. E. eds., Series in BioEngineering. Springer Berlin Heidelberg
-
Fabbrocini, G.; Vita, V.; Cacciapuoti, S.; Leo, G.; Liguori, C.; Paolillo, A.; Pietrosanto, A.; and Sommella, P. 2014. Automatic diagnosis of melanoma based on the 7-point checklist. In Scharcanski, J., and Celebi, M. E., eds., Computer Vision Techniques for the Diagnosis of Skin Cancer, Series in BioEngineering. Springer Berlin Heidelberg. 71-107.
-
(2014)
Computer Vision Techniques for the Diagnosis of Skin Cancer
, pp. 71-107
-
-
Fabbrocini, G.1
Vita, V.2
Cacciapuoti, S.3
Leo, G.4
Liguori, C.5
Paolillo, A.6
Pietrosanto, A.7
Sommella, P.8
-
12
-
-
85046105427
-
Attributes for improved attributes: A multi-task network for attribute classification
-
abs/1604.07360
-
Hand, E. M., and Chellappa, R. 2016. Attributes for improved attributes: A multi-task network for attribute classification. CoRR abs/1604.07360.
-
(2016)
CoRR
-
-
Hand, E.M.1
Chellappa, R.2
-
13
-
-
84958589374
-
Deep residual learning for image recognition
-
abs/1512.03385
-
He, K.; Zhang, X.; Ren, S.; and Sun, J. 2015. Deep residual learning for image recognition. CoRR abs/1512.03385.
-
(2015)
CoRR
-
-
He, K.1
Zhang, X.2
Ren, S.3
Sun, J.4
-
14
-
-
84913580146
-
Caffe: Convolutional architecture for fast feature embedding
-
MM'14, Orlando, FL, USA, November 03 - 07
-
Jia, Y.; Shelhamer, E.; Donahue, J.; Karayev, S.; Long, J.; Girshick, R. B.; Guadarrama, S.; and Darrell, T. 2014. Caffe: Convolutional architecture for fast feature embedding. In Proceedings of the ACM International Conference on Multimedia, MM'14, Orlando, FL, USA, November 03 - 07, 2014, 675-678.
-
(2014)
Proceedings of the ACM International Conference on Multimedia
, pp. 675-678
-
-
Jia, Y.1
Shelhamer, E.2
Donahue, J.3
Karayev, S.4
Long, J.5
Girshick, R.B.6
Guadarrama, S.7
Darrell, T.8
-
15
-
-
84978426890
-
Deep features to classify skin lesions
-
ISBI 2016, Prague, Czech Republic, April 13-16
-
Kawahara, J.; BenTaieb, A.; and Hamarneh, G. 2016. Deep features to classify skin lesions. In 13th IEEE International Symposium on Biomedical Imaging, ISBI 2016, Prague, Czech Republic, April 13-16, 2016, 1397-1400.
-
(2016)
13th IEEE International Symposium on Biomedical Imaging
, pp. 1397-1400
-
-
Kawahara, J.1
BenTaieb, A.2
Hamarneh, G.3
-
16
-
-
84876231242
-
Imagenet classification with deep convolutional neural networks
-
Proceedings of a meeting held December 3-6, 2012, Lake Tahoe, Nevada, United States
-
Krizhevsky, A.; Sutskever, I.; and Hinton, G. E. 2012. Imagenet classification with deep convolutional neural networks. In Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012, Lake Tahoe, Nevada, United States., 1106-1114.
-
(2012)
Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012
, pp. 1106-1114
-
-
Krizhevsky, A.1
Sutskever, I.2
Hinton, G.E.3
-
18
-
-
85019114938
-
Skin disease classification versus skin lesion characterization: Achieving robust diagnosis using multi-label deep neural networks
-
Liao, H.; Li, Y.; and Luo, J. 2016. Skin disease classification versus skin lesion characterization: Achieving robust diagnosis using multi-label deep neural networks. In International Conference on Pattern Recognition (ICPR).
-
(2016)
International Conference on Pattern Recognition (ICPR)
-
-
Liao, H.1
Li, Y.2
Luo, J.3
-
19
-
-
84906493406
-
Microsoft COCO: Common objects in context
-
Zurich, Switzerland, September 6-12, 2014, Proceedings
-
Lin, T.; Maire, M.; Belongie, S. J.; Hays, J.; Perona, P.; Ramanan, D.; Dollar, P.; and Zitnick, C. L. 2014. Microsoft COCO: common objects in context. In Computer Vision - ECCV 2014 - 13th European Conference, Zurich, Switzerland, September 6-12, 2014, Proceedings, Part 5, 740-755.
-
(2014)
Computer Vision - ECCV 2014 - 13th European Conference
, pp. 740-755
-
-
Lin, T.1
Maire, M.2
Belongie, S.J.3
Hays, J.4
Perona, P.5
Ramanan, D.6
Dollar, P.7
Zitnick, C.L.8
-
20
-
-
85016118349
-
Hyperface: A deep multi-task learning framework for face detection, landmark localization, pose estimation, and gender recognition
-
abs/1603.01249
-
Ranjan, R.; Patel, V. M.; and Chellappa, R. 2016. Hyperface: A deep multi-task learning framework for face detection, landmark localization, pose estimation, and gender recognition. CoRR abs/1603.01249.
-
(2016)
CoRR
-
-
Ranjan, R.1
Patel, V.M.2
Chellappa, R.3
-
21
-
-
84908537903
-
CNN features off-the-shelf: An astounding baseline for recognition
-
CVPR Workshops 2014, Columbus, OH, USA, June 23-28, 2014
-
Razavian, A. S.; Azizpour, H.; Sullivan, J.; and Carlsson, S. 2014. CNN features off-the-shelf: An astounding baseline for recognition. In IEEE Conference on Computer Vision and Pattern Recognition, CVPR Workshops 2014, Columbus, OH, USA, June 23-28, 2014, 512-519.
-
(2014)
IEEE Conference on Computer Vision and Pattern Recognition
, pp. 512-519
-
-
Razavian, A.S.1
Azizpour, H.2
Sullivan, J.3
Carlsson, S.4
-
22
-
-
84960980241
-
Faster R-CNN: Towards real-time object detection with region proposal networks
-
December 7-12, 2015, Montreal, Quebec, Canada
-
Ren, S.; He, K.; Girshick, R. B.; and Sun, J. 2015. Faster R-CNN: towards real-time object detection with region proposal networks. In Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, December 7-12, 2015, Montreal, Quebec, Canada, 91-99.
-
(2015)
Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015
, pp. 91-99
-
-
Ren, S.1
He, K.2
Girshick, R.B.3
Sun, J.4
-
23
-
-
84947041871
-
Imagenet large scale visual recognition challenge
-
Russakovsky, O.; Deng, J.; Su, H.; Krause, J.; Satheesh, S.; Ma, S.; Huang, Z.; Karpathy, A.; Khosla, A.; Bernstein, M. S.; Berg, A. C.; and Li, F. 2015. Imagenet large scale visual recognition challenge. International Journal of Computer Vision 115(3):211-252.
-
(2015)
International Journal of Computer Vision
, vol.115
, Issue.3
, pp. 211-252
-
-
Russakovsky, O.1
Deng, J.2
Su, H.3
Krause, J.4
Satheesh, S.5
Ma, S.6
Huang, Z.7
Karpathy, A.8
Khosla, A.9
Bernstein, M.S.10
Berg, A.C.11
Li, F.12
-
24
-
-
84933585162
-
Very deep convolutional networks for large-scale image recognition
-
abs/1409.1556
-
Simonyan, K., and Zisserman, A. 2014. Very deep convolutional networks for large-scale image recognition. CoRR abs/1409.1556.
-
(2014)
CoRR
-
-
Simonyan, K.1
Zisserman, A.2
-
25
-
-
84901804555
-
Cascaded ensemble of convolutional neural networks and handcrafted features for mitosis detec-tion
-
90410B-90410B. International Society for Optics and Photonics
-
Wang, H.; Cruz-Roa, A.; Basavanhally, A.; Gilmore, H.; Shih, N.; Feldman, M.; Tomaszewski, J.; Gonzalez, F.; and Madabhushi, A. 2014. Cascaded ensemble of convolutional neural networks and handcrafted features for mitosis detec-tion. In SPIE Medical Imaging, 90410B-90410B. International Society for Optics and Photonics.
-
(2014)
SPIE Medical Imaging
-
-
Wang, H.1
Cruz-Roa, A.2
Basavanhally, A.3
Gilmore, H.4
Shih, N.5
Feldman, M.6
Tomaszewski, J.7
Gonzalez, F.8
Madabhushi, A.9
-
26
-
-
85008921966
-
Dermoscopy image processing for Chinese
-
Scharcanski, J. and Celebi, M. E. eds., Series in BioEngineering. Springer Berlin Heidelberg
-
Xie, F.; Wu, Y.; Jiang, Z.; and Meng, R. 2014. Dermoscopy image processing for Chinese. In Scharcanski, J., and Celebi, M. E., eds., Computer Vision Techniques for the Diagnosis of Skin Cancer, Series in BioEngineering. Springer Berlin Heidelberg. 109-137.
-
(2014)
Computer Vision Techniques for the Diagnosis of Skin Cancer
, pp. 109-137
-
-
Xie, F.1
Wu, Y.2
Jiang, Z.3
Meng, R.4
-
27
-
-
84906489074
-
Visualizing and understanding convolutional networks
-
Zurich, Switzerland, September 6-12, Proceedings, Parti
-
Zeiler, M. D., and Fergus, R. 2014. Visualizing and understanding convolutional networks. In Computer Vision - ECCV 2014 - 13th European Conference, Zurich, Switzerland, September 6-12, 2014, Proceedings, Parti, 818-833.
-
(2014)
Computer Vision - ECCV 2014 - 13th European Conference
, pp. 818-833
-
-
Zeiler, M.D.1
Fergus, R.2
-
28
-
-
84963829815
-
Learning deep representation for face alignment with auxiliary attributes
-
Zhang, Z.; Luo, P.; Loy, C. C.; and Tang, X. 2016. Learning deep representation for face alignment with auxiliary attributes. IEEE Trans. Pattern Anal. Mach. Intell. 38(5):918- 930.
-
(2016)
IEEE Trans. Pattern Anal. Mach. Intell.
, vol.38
, Issue.5
, pp. 918-930
-
-
Zhang, Z.1
Luo, P.2
Loy, C.C.3
Tang, X.4
|