Burak Uzkent

Burak Uzkent

Machine Learning Scientist

Peer-Reviewed Journal Papers

  1. E. Velterop, B. Uzkent, J. Suckale, ‘‘Safe Shelter: A Case for Prioritizing Housing Quality in Climate Adaptation Policy by Remotely Sensing Roof Tarps in the San Francisco Bay Area’’, In Earth’s Future, 2022

  2. B. Uzkent, A. Rangnekar, M.J. Hoffman, ‘‘Tracking in Aerial Hyperspectral Videos using Deep Kernelized Correlation Filters’’, In IEEE Transactions on Geoscience and Remote Sensing, 2019 PDF arxiv code

  3. B. Uzkent, M. J. Hoffman, A. Vodacek, ‘‘Integrating Hyperspectral Likelihoods in a Multi-dimensional Assignment Algorithm for Aerial Vehicle Tracking’’, In IEEE Journal of Selected Topics in Remote Sensing and Observation, 9(9): 4325–4333, May 2016. PDF code

  4. B. Uzkent, M. J. Hoffman, A. Vodacek, Bin Chen, ‘‘Feature Matching with an Adaptive Optical Sensor in a Ground Target Tracking System’’, In IEEE Sensors Journal, 15(1): 510–519, January 2015. PDF

  5. B. Uzkent, B.D. Barkana, H. Cevikalp, ‘‘Non-speech environmental sound classification using SVMS with a new set of features’’, In International Journal of Innovative Computing, Information and Control, 8(5): 3511–3524, May 2012. PDF

  6. B.D. Barkana, B. Uzkent, I. Saricicek, ‘‘Normal and abnormal non-speech audio event detection using MFCC and PR-based feature sets’’, In Advanced Materials Research, Volume 601, pp: 200–208, December 2012.

  7. B.D. Barkana, B. Uzkent, I. Saricicek, ‘‘Environmental noise classifier using a new set of feature parameters based on pitch range’’, In Applied Acoustics, 72(11): 841–848, November 2011. PDF

  8. B. Uzkent, B.D. Barkana, J. Yang, ‘‘Automatic environmental noise source classification model using fuzzy logic’’, In Expert Systems with Applications, 38(7): 8751–8755, July 2011. PDF

Peer-Reviewed Conference Papers

  1. K. Doshi, A. Garg, B. Uzkent, X. Wang, M. Omar, “A Multimodal Benchmark and Improved Architecture for Zero Shot Learning.”, In Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision. 2024

  2. J. Yi, B. Uzkent, O. Ignat, Z. Li, A. Garg, X. Yu, L. Liu, “Augment the Pairs: Semantics-Preserving Image-Caption Pair Augmentation for Grounding-Based Vision and Language Models.”, In Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision. 2024.

  3. B. Uzkent, A. Garg, W. Zhou, K. Doshi, J. Yi, X. Wang, M. Omar, “Dynamic Inference with Grounding Based Vision and Language Models.”, In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. 2023.

  4. S. Gao, B. Uzkent, Y. Shen, H. Huang, H. Jin, “Learning to Jointly Share and Prune Weights for Grounding Based Vision and Language Models.”, In The Eleventh International Conference on Learning Representations. 2022.

  5. M. Yin, B. Uzkent, Y. Shen, H. Jin, “GOHSP: A Unified Framework of Graph and Optimization-based Heterogeneous Structured Pruning for Vision Transformer”, The 37th AAAI Conference on Artificial Intelligence, February 2023.

  6. S. Chakraborty, B. Uzkent, K. Ayush, E. Sheehan, S. Ermon, “Efficient Conditional Pre-training for Transfer Learning”, International Conference on Computer Vision and Pattern Recognition Workshops, June 2022. Arxiv

  7. Q. Lu, Y.C. Shu, B. Uzkent, T. Hua, Y. Shen, H. Jin, “Lite-MDETR: A Lightweight Multi-Modal Detector”, International Conference on Computer Vision and Pattern Recognition, June 2022.

  8. B. Uzkent, K. Ayush, C. Meng, M. Burke, D. Lobell, S. Ermon, “Geography-Aware Self-Supervised Learning”, International Conference on Computer Vision, October 2021. PDF code webpage

  9. K. Ayush, A. Sinha, J. Song, B. Uzkent, H. Jin, S. Ermon, “Negative Data Augmentation”, In Proceedings of The International Conference on Learning Representations, May 2021. PDF code

  10. B. Uzkent, K. Ayush, M. Burke, D. Lobell, S. Ermon, “Efficient High Resolution Image Processing using Deep Reinforcement Learning”, In Proceedings of The Thirty-Fourth AAAI Conference on Artificial Intelligence, January 2021. arxiv

  11. J. Lee, D. Grosz, B. Uzkent, S. Zheng, M. Burke, D. Lobell, S. Ermon, “Predicting Geo-attributes Using Deep Learning and Publicly Available Street-level Images”, In Proceedings of The Thirty-Fourth AAAI Conference on Artificial Intelligence, January 2021. arxiv code

  12. K. Ayush, B. Uzkent, M. Burke, D. Lobell, S. Ermon, “Generating Interpretable Poverty Maps Using Object Detection in Satellite Images”, In Proceedings of International Joint Conference on Artificial Intelligence, August 2020. arxiv PDF

  13. B. Uzkent, S. Ermon, “Learning When and Where to Zoom Using Deep Reinforcement Learning”, In Proceedings of IEEE Computer Vision and Pattern Recognition, July 2020 (Oral). arxiv PDF code

  14. H.L. Aung, B. Uzkent, M. Burke, D. Lobell, S. Ermon, “Farmland Parcel Delineation using Spatio-temporal Convolutional Networks”, In Proceedings of the Agriculture-Vision: Challenges & Opportunities for Computer Vision in Agriculture, In conjunction with Computer Vision and Pattern Recognition, June 2020. PDF code

  15. V. Sarukkai, A. Jain, B. Uzkent, S. Ermon, “Cloud Removal from Satellite Images Using Spatiotemporal Generator Networks”, In Proceedings of IEEE Winter Conference of Applications of Computer Vision (WACV), March 2020. arxiv PDF code

  16. B. Uzkent, C. Yeh, S. Ermon, “Efficient Object Detection in Large Images Using Deep Reinforcement Learning”, In Proceedings of IEEE Winter Conference of Applications of Computer Vision (WACV), March 2020. arxiv PDF code

  17. B. Uzkent, E. Sheehan, C. Meng, Z. Tang, D. Lobell, M. Burke, S. Ermon, “Learning How to Interpret Satellite Images using Wikipedia,” In Proceedings of the International Joint Conference on Artificial Intelligence, 2019. arxiv PDF Code

  18. E. Sheehan, C. Meng, M. Tan, B. Uzkent, N. Jean, D. Lobell, M. Burke, S. Ermon, “Predicting Economic Development using Geolocated Wikipedia Articles,” In Proceedings of 25TH ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2019. PDF code

  19. B. Uzkent, Y. Seo, “EnKCF: Ensemble of Kernelized Correlation Filters for High-Speed Object Tracking,” In Proceedings of IEEE Winter Conference on Applications of Computer Vision (WACV), pp. 1133-1141, March 2018. PDF code

  20. B. Uzkent, A. Rangnekar, M. J. Hoffman, A. Vodacek, ‘‘Aerial Vehicle Tracking by Adaptive Fusion of Likelihood Maps’’, In Proceedings of the 13th IEEE Workshop on Perception Beyond the Visible Spectrum, In conjunction with Computer Vision and Pattern Recognition 2017. PDF code

  21. B. Uzkent, M. J. Hoffman, A. Vodacek, ‘‘Real-time Target Detection and Tracking in Aerial Video using Hyperspectral Features,” In Proceedings of the 1st IEEE Workshop on Moving Cameras Meet Video Surveillance: From Body Cameras to Drones, In conjunction with Computer Vision and Pattern Recognition 2016, pp. 36–44. June 2016. PDF code

  22. B. Uzkent, M. J. Hoffman, A. Vodacek, ‘‘Spectral Validation of Measurements in a Vehicle Tracking DDDAS’’, In Proceedings of International Conference on Computational Science, Volume 51, pp. 2493–2502, June 2015. PDF

  23. B. Uzkent, M. J. Hoffman, A. Vodacek, ‘‘Background Image Understanding and Adaptive Imaging for Vehicle Tracking’’, In Proceedings of the SPIE 9460, Airborne Intelligence, Surveillance, Reconnaissance (ISR) Systems and Applications XII, pp. -94600F–94600F-7, April 2015. PDF

  24. B. Uzkent, M. J. Hoffman, A. Vodacek, ‘‘Efficient Integration of Spectral Features for Vehicle Tracking utilizing an Adaptive Sensor’’, In Proceedings of the SPIE 9407, Video Surveillance and Transportation Imaging Applications, pp. 940707–940707-10, February 2015. PDF

  25. B. Uzkent, M. J. Hoffman, A. Vodacek, ‘. B. Uzkent, M. J. Hoffman, E. Cherry, N. Cahill, ‘‘3-D MRI Cardiac Segmentation using Graph Cuts’’, In Proceedings of the IEEE Western NY Image Processing Workshop, pp. 47–51, Rochester, NY, November 2014. PDF code

  26. B. Uzkent, M. J. Hoffman, A. Vodacek, J. P. Kerekes, B. Chen, ‘‘Feature matching and adaptive prediction models in an object tracking DDDAS’’, In Proceedings of Procedia Computer Science, Volume 18, pp. 1939-1948, 2013. PDF

  27. B. Uzkent, B.D. Barkana, ‘‘Pitch range-based feature extraction for audio surveillance systems’’, In Proceedings of IEEE International Conference on Information Technology: New Generations (ITNG), pp. 476–480, April 11-13, 2011. PDF

  28. B.D. Barkana, I. Saricicek, B. Uzkent, ‘‘Performances of the ANN, SVM, and K-means clustering methods recognizing different environmental sounds’’, In Proceedings of the 24th European Conference on Operational Research, Lisbon, Portugal, July 11-14, 2010.

  29. B. Uzkent, O. Parlaktuna, ‘‘Autonomous parallel parking of non-holonomic vehicles’’, In Proceedings of the 13th National Conference in Middle East Technical University, Ankara, Turkey, 2009.

Preprints

  1. B. Uzkent, S. Ermon, “Domain Adaptation Using Adversarial Learning for Studying Low Resolution Images”. Arxiv

  2. B. Uzkent, E. Sheehan, C. Meng, Z. Tang, M. Burke, D. Lobell, S. Ermon, ‘‘Learning to Interpret Satellite Images in Global Scale Using Wikipedia’’. Arxiv

  3. E. Sheehan, B. Uzkent, C. Meng, Z. Tang, M. Burke, D. Lobell, S. Ermon, ‘‘Learning to interpret satellite images using wikipedia’’. Arxiv