Dimitris Samaras
Affiliations: | Computer Science | Stony Brook University, Stony Brook, NY, United States |
Area:
Computer vision; machine learning; computational behavioral sciences; computer graphics; medical imaging; computational photography.Google:
"Dimitris Samaras"Children
Sign in to add traineeAlexandros Panagopoulos | grad student | 2011 | SUNY Stony Brook |
Jean F. Honorio Carrillo | grad student | 2012 | SUNY Stony Brook |
Yun Zeng | grad student | 2012 | SUNY Stony Brook |
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Publications
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Fassler DJ, Abousamra S, Gupta R, et al. (2020) Deep learning-based image analysis methods for brightfield-acquired multiplex immunohistochemistry images. Diagnostic Pathology. 15: 100 |
Hou L, Yago Vicente T, Hoai M, et al. (2019) Large scale shadow annotation and detection using lazy annotation and stacked CNNs. Ieee Transactions On Pattern Analysis and Machine Intelligence |
Hou L, Nguyen V, Kanevsky AB, et al. (2019) Sparse Autoencoder for Unsupervised Nucleus Detection and Representation in Histopathology Images. Pattern Recognition. 86: 188-200 |
Wang M, Shu Z, Cheng S, et al. (2019) An adversarial neuro-tensorial approach for learning disentangled representations International Journal of Computer Vision. 127: 743-762 |
Yago Vicente TF, Hoai M, Samaras D. (2017) Leave-one-out Kernel Optimization for Shadow Detection and Removal. Ieee Transactions On Pattern Analysis and Machine Intelligence |
Shu Z, Hadap S, Shechtman E, et al. (2017) Portrait lighting transfer using a mass transport approach Acm Transactions On Graphics. 36: 1 |
Zeng Y, Wang C, Gu X, et al. (2016) Higher-order Graph Principles towards Non-rigid Surface Registration. Ieee Transactions On Pattern Analysis and Machine Intelligence |
Shu Z, Shechtman E, Samaras D, et al. (2016) EyeOpener: Editing eyes in the wild Acm Transactions On Graphics. 36 |
Yun K, Ge G, Samaras D, et al. (2015) How we look tells us what we do: Action recognition using human gaze. Journal of Vision. 15: 121 |
Yu CP, Samaras D, Zelinsky GJ. (2014) Modeling visual clutter perception using proto-object segmentation. Journal of Vision. 14 |