| Sun attribute database: Discovering, annotating, and recognizing scene attributes G Patterson, J Hays 2012 IEEE Conference on Computer Vision and Pattern Recognition, 2751-2758, 2012 | 538 | 2012 |
| The sun attribute database: Beyond categories for deeper scene understanding G Patterson, C Xu, H Su, J Hays International Journal of Computer Vision 108 (1-2), 59-81, 2014 | 278 | 2014 |
| Coco attributes: Attributes for people, animals, and objects G Patterson, J Hays European Conference on Computer Vision, 85-100, 2016 | 42 | 2016 |
| Rnnbow: Visualizing learning via backpropagation gradients in recurrent neural networks D Cashman, G Patterson, A Mosca, R Chang Workshop on Visual Analytics for Deep Learning (VADL) 4, 2017 | 29* | 2017 |
| Simple modeling and prototype experiments for a new high-thrust low-speed permanent-magnet disk motor G Patterson, T Koseki, Y Aoyama, K Sako IEEE Transactions on Industry Applications 47 (1), 65-71, 2010 | 26 | 2010 |
| Tropel: Crowdsourcing detectors with minimal training G Patterson, G Van Horn, S Belongie, P Perona, J Hays Proceedings of the AAAI Conference on Human Computation and Crowdsourcing 3 (1), 2015 | 20 | 2015 |
| Basic level scene understanding: categories, attributes and structures J Xiao, J Hays, BC Russell, G Patterson, K Ehinger, A Torralba, A Oliva Frontiers in psychology 4, 506, 2013 | 18 | 2013 |
| Lean multiclass crowdsourcing G Van Horn, S Branson, S Loarie, S Belongie, P Perona Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2018 | 14 | 2018 |
| Crowd-guided ensembles: How can we choreograph crowd workers for video segmentation? A Kaspar, G Patterson, C Kim, Y Aksoy, W Matusik, M Elgharib Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems …, 2018 | 9 | 2018 |
| Dynamics of Fluids and Plasmas GS Patterson, S Corrsin Academic, New York, 1966 | 9 | 1966 |
| Expert identification of visual primitives used by CNNs during mammogram classification J Wu, D Peck, S Hsieh, V Dialani, CD Lehman, B Zhou, V Syrgkanis, ... Medical Imaging 2018: Computer-Aided Diagnosis 10575, 105752T, 2018 | 8 | 2018 |
| Deepminer: Discovering interpretable representations for mammogram classification and explanation J Wu, B Zhou, D Peck, S Hsieh, V Dialani, L Mackey, G Patterson arXiv preprint arXiv:1805.12323, 2018 | 7 | 2018 |
| Bootstrapping fine-grained classifiers: Active learning with a crowd in the loop G Patterson, G Van, H Serge, B Pietro, PJ Hays | 6 | 2013 |
| The physician assistant in primary care: a proposal for British Columbia’s health care system I Brethour, G Carlson, G Patterson, C Sun, T Williams Victoria, BC: BC Ministry of Health, 1994 | 5 | 1994 |
| Visual state feedback digital control of a linear synchronous motor using generic video-camera signal T Koseki, G Patterson, T Suzuki 2008 International Conference on Electrical Machines and Systems, 1095-1100, 2008 | 3 | 2008 |
| Humor in Word Embeddings: Cockamamie Gobbledegook for Nincompoops L Gultchin, G Patterson, N Baym, N Swinger, AT Kalai arXiv preprint arXiv:1902.02783, 2019 | 2 | 2019 |
| The SUN Attribute Database: Organizing Scenes by Affordances, Materials, and Layout G Patterson, J Hays Visual Attributes, 269-297, 2017 | 1 | 2017 |
| Using humans to build mid-level features G Patterson, TY Lin, J Hays, S Diego IEEE Conf. on Computer Vision and Pattern Recognition Workshop 44, 2013 | 1 | 2013 |
| Modeling and Prototype Experiments for a New High-Thrust, Low-Speed Permanent Magnet Synchronous Motor JS Shin, G Patterson, K Sato, K Sako, T Koseki, Y Aoyama The 10th University of Tokyo-SNU Joint Seminar on Electrical Engineering, 2010 | 1 | 2010 |
| Genevieve Patterson G Patterson, G Van Horn, S Belongie, P Perona, J Hays, BFG Classiers, ... | | 2013 |
James HaysGeorgia TechVerified email at gatech.edu
