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

  • 3 Similar Profiles
Cameras Engineering & Materials Science
Pixels Engineering & Materials Science
Textures Engineering & Materials Science
Motion estimation Engineering & Materials Science
Computer vision Engineering & Materials Science
Trajectories Engineering & Materials Science
Imaging techniques Engineering & Materials Science
Image segmentation Engineering & Materials Science

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Research Output 1978 2018

Joint Estimation of Human Pose and Conversational Groups from Social Scenes

Varadarajan, J., Subramanian, R., Bulò, S. R., Ahuja, N., Lanz, O. & Ricci, E. Apr 1 2018 In : International Journal of Computer Vision. 126, 2-4, p. 410-429 20 p.

Research output: Contribution to journalArticle

Supervised learning
Learning algorithms
Cameras
Experiments

Superpixel Hierarchy

Wei, X., Yang, Q., Gong, Y., Ahuja, N. & Yang, M. H. May 16 2018 (Accepted/In press) In : IEEE Transactions on Image Processing.

Research output: Contribution to journalArticle

Computer vision
Detectors

Active online anomaly detection using dirichlet process mixture model and Gaussian process classification

Varadarajan, J., Subramanian, R., Ahuja, N., Moulin, P. & Odobez, J. M. May 11 2017 Proceedings - 2017 IEEE Winter Conference on Applications of Computer Vision, WACV 2017. Institute of Electrical and Electronics Engineers Inc., p. 615-623 9 p. 7926657

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

Labeling
Unsupervised learning
Video streaming
Labels
Problem-Based Learning

Clustering Through Hybrid Network Architecture With Support Vectors

Ergul, E., Arica, N., Ahuja, N. & Erturk, S. Jun 1 2017 In : IEEE Transactions on Neural Networks and Learning Systems. 28, 6, p. 1373-1385 13 p., 7442845

Research output: Contribution to journalArticle

Network architecture
Support vector machines
Tuning
Neural networks
Self organizing maps

Deep laplacian pyramid networks for fast and accurate super-resolution

Lai, W. S., Huang, J. B., Ahuja, N. & Yang, M. H. Nov 6 2017 Proceedings - 30th IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2017. Institute of Electrical and Electronics Engineers Inc., Vol. 2017-January, p. 5835-5843 9 p.

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

Image resolution
Convolution
Computational complexity
Interpolation
Neural networks