Search Publication
. Active Deep Learning for Medical Imaging Segmentation. In Medical Image meets NIPS 2017 Workshop. 2017.  (187.43 KB)
 (187.43 KB)
 (187.43 KB)
 (187.43 KB). Active Deep Learning for Medical Imaging Segmentation. . 2017.  (2.84 MB)
 (2.84 MB)
 (2.84 MB)
 (2.84 MB). Cost-Effective Active Learning for Melanoma Segmentation. In ML4H: Machine Learning for Health Workshop at NIPS 2017. Long Beach, CA, USA; 2017.  (521.82 KB)
 (521.82 KB)
 (521.82 KB)
 (521.82 KB). Assessment of Crowdsourcing and Gamification Loss in User-Assisted Object Segmentation. Multimedia Tools and Applications. 2016;23(75).  (5.05 MB)
 (5.05 MB)
 (5.05 MB)
 (5.05 MB). Co-filtering human interaction and object segmentation. . 2015.  (1.82 MB)
 (1.82 MB)
 (1.82 MB)
 (1.82 MB). Quality Control in Crowdsourced Object Segmentation. In IEEE International Conference on Image Processing (ICIP), 2015. 2015.  (362.33 KB)
 (362.33 KB)
 (362.33 KB)
 (362.33 KB). Click’n’Cut: Crowdsourced Interactive Segmentation with Object Candidates. In 3rd International ACM Workshop on Crowdsourcing for Multimedia (CrowdMM). Orlando, Florida (USA); 2014.  (1017.73 KB)
 (1017.73 KB)
 (1017.73 KB)
 (1017.73 KB). Crowdsourced Object Segmentation with a Game. . 2013.  (1.34 MB)
 (1.34 MB)
 (1.34 MB)
 (1.34 MB). Crowdsourced Object Segmentation with a Game. In ACM Workshop on Crowdsourcing for Multimedia (CrowdMM). Barcelona; 2013.  (1.22 MB)
 (1.22 MB)
 (1.22 MB)
 (1.22 MB) 
       ]
]