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Fingerprint Fingerprint is based on mining the text of the experts' scientific documents to create an index of weighted terms, which defines the key subjects of each individual researcher.

  • 19 Similar Profiles
Robots Engineering & Materials Science
Semantics Engineering & Materials Science
Human robot interaction Engineering & Materials Science
Robotics Engineering & Materials Science
Experiments Engineering & Materials Science
End effectors Engineering & Materials Science
Neural networks Engineering & Materials Science
Computer vision Engineering & Materials Science

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Research Output 2009 2018

  • 395 Citations
  • 11 h-Index
  • 30 Conference contribution
  • 7 Article
  • 1 Review article
3 Citations

Convolutional neural networks: Ensemble modeling, fine-tuning and unsupervised semantic localization for neurosurgical CLE images

Izadyyazdanabadi, M., Belykh, E., Mooney, M., Martirosyan, N., Eschbacher, J., Nakaji, P., Preul, M. C. & Yang, Y., Jul 1 2018, In : Journal of Visual Communication and Image Representation. 54, p. 10-20 11 p.

Research output: Contribution to journalArticle

Tuning
Semantics
Surgery
Neural networks
Tumors

Interpretable partitioned embedding for customized multi-item fashion outfit composition

Feng, Z., Yu, Z., Yang, Y., Jing, Y., Jiang, J. & Song, M., Jun 5 2018, ICMR 2018 - Proceedings of the 2018 ACM International Conference on Multimedia Retrieval. Association for Computing Machinery, Inc, p. 143-151 9 p.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Chemical analysis
Labels
Industry
Experiments
Deep learning
1 Citations

Prospects for theranostics in neurosurgical imaging: Empowering confocal laser endomicroscopy diagnostics via deep learning

Izadyyazdanabadi, M., Belykh, E., Mooney, M. A., Eschbacher, J. M., Nakaji, P., Yang, Y. & Preul, M. C., Jul 3 2018, In : Frontiers in Oncology. 8, JUL, 240.

Research output: Contribution to journalReview article

Lasers
Learning
Brain Neoplasms
Optical Imaging
Fluorescence

Stroke controllable fast style transfer with adaptive receptive fields

Jing, Y., Liu, Y., Yang, Y., Feng, Z., Yu, Y., Tao, D. & Song, M., Jan 1 2018, Computer Vision – ECCV 2018 - 15th European Conference, 2018, Proceedings. Ferrari, V., Sminchisescu, C., Weiss, Y. & Hebert, M. (eds.). Springer Verlag, p. 244-260 17 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 11217 LNCS).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Receptive Field
Stroke
Style
Control Strategy
Distinct

Weakly-supervised learning-based feature localization for confocal laser endomicroscopy glioma images

Izadyyazdanabadi, M., Belykh, E., Cavallo, C., Zhao, X., Gandhi, S., Moreira, L. B., Eschbacher, J., Nakaji, P., Preul, M. C. & Yang, Y., Jan 1 2018, Medical Image Computing and Computer Assisted Intervention – MICCAI 2018 - 21st International Conference, 2018, Proceedings. Fichtinger, G., Davatzikos, C., Alberola-López, C., Frangi, A. F. & Schnabel, J. A. (eds.). Springer Verlag, p. 300-308 9 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 11071 LNCS).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Confocal
Supervised learning
Supervised Learning
Laser
Lasers

Projects 2017 2023