Publications

Publications

RDSC scientists routinely publish research across a wide variety of disciplines that include autonomous transportation, Bayesian statistics, image processing, machine learning and medical informatics – to name a few. A list of our recent publications are below:

2019

  • A. Smith, G. P. Dietl, J. C. Handley (2019). Durophagy bias: The effect of shell destruction by crushing predators on drilling frequency, forthcoming in Palaeogeography, Palaeoclimatology, Palaeoecology, 514, pp. 690-694. – link
  • Adams, M., Boslett, A., Denham, A., Hill, E. “Unclassified drug overdose deaths in the opioid crisis: Emerging patterns of inequality.” 2019. Journal of the American Medical Informatics Association, ocz050. – link
  • Andrew Boslett, Todd Guilfoos, and Corey Lang, “Valuation of the External Costs of Unconventional Oil and Gas Development: The Critical Importance of Mineral Rights Ownership,” Journal of the Association of Environmental and Resource Economists 6, no. 3 (May 2019): 531-561. – link
  • Boslett, A., Hill, E. “Shale Gas Transmission Pipelines and Housing Prices.” 2019. Resource and Energy Economics 57: 36-50. – link
  • J. C. Handley, L. Fu and L. L. Tupper (2019). A case study in spatial-temporal accessibility for a transit system, Journal of Transport Geography, 75, pp. 25-36. – link
  • E. Bernal, Q. Li. Foreground-aware Statistical Models for Background Estimation, Electronic Imaging, San Francisco, CA, Jan. 2019. – link
  • E. Bernal. Surrogate Contrastive Network for Supervised Band Selection in Multispectral Image Analysis Tasks, IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), June 2019. – link
  • E. Bernal. Towards Robust Neural Networks, Move78* Artificial Intelligence Seminar series, Rochester Institute of Technology, Rochester, NY, April 2019. – link
  • Gavai, W. Wu, B. Xu, et. al., “Hybrid Image-based Defect Detection for Railroad Maintenance,” 2019 IS&T International Symposium on Electronic Imaging, Jan. 13-17, 2019, Burlingame, CA. – link
  • K. G. Lore, K. Reddy, M. Giering, E. Bernal. Generative Adversarial Networks for Spectral Super-resolution and bidirectional RGB-to-multispectral mapping, 2019 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), June 2019. – link
  • L. Lin, B. Xu, W. Wu, T. Richardson, E. A. Bernal, B. Martens, C. Thornton, C. Heatwole, “Deep Metric Learning with Triplet Networks: Application to Hand-grip Myotonia,” IEEE EMB Special Topic Conference on Healthcare Innovations and Point-of-Care Technologies, 2019.
  • Lei Lin, Beilei Xu, Wencheng Wu, Trevor W. Richardson, and Edgar A. Bernal. “Medical Time Series Classification with Hierarchical Attention-based Temporal Convolutional Networks: A Case Study of Myotonic Dystrophy Diagnosis.” In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, pp. 83-86. 2019. – link
  • Li, Tao, and Lei Lin. “AnonymousNet: Natural face de-identification with measurable privacy.” In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, pp. 0-0. 2019. – link
  • Lishan Liu, Ning Jia, Lei Lin, and Zhengbing He. “A cohesion-based heuristic feature selection for short-term traffic forecasting.” IEEE Access 7 (2019): 2169-3536. – link
  • Shreve, R. Bala, W. Wu, B. Xu, P. Matts, A, Purwar, “Deep CNNs for Facial Skin Age Modeling,” accepted to International Conference on Machine Vision Applications, May 27–31 2019, Tokyo, Japan. – link
  • O. Oshin, E. Bernal, B. Nair, J. Ding, R. Varma, R. Osborne, E. Tunstel, F. Stramandinoli. Coupling Deep Discriminative and Generative Models for Reactive Robot Planning in Human-Robot Collaboration, in Proc. 2019 IEEE Conference on Systems, Man and Cybernetics.
  • Ren, Shuyun, Fengji Luo, Lin Lei, Shu-Chien Hsu, and Xuran Ivan Li. “A novel dynamic pricing scheme for a large-scale electric vehicle sharing network considering vehicle relocation and vehicle-grid-integration.” International Journal of Production Economics (2019). – link
  • T. Cheng, B. Xu, W. Wu, L. Lin, T. Richardson, and E. A. Bernal, “An Unsupervised Machine Learning Framework for Parkinson’s Disease Progression Analysis and Subtyping,” IEEE EMB Special Topic Conference on Healthcare Innovations and Point-of-Care Technologies, 2019.
  • T. Wang, Y. Gu, X. Zhao, D. Mehta, E. Bernal. Improving the Sensitivity of Neural Networks to Adversarial Attacks, 2019 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), June 2019.
  • Voelkel, J.G. (2019). The Design of Order-of-Addition Experiments, Journal of Quality Technology, 51, 230-241. – link
  • Wu, W., “On-street parked vehicle detection via view-normalized classifier,” IS&T International Symposium on Electronic Imaging 2019: Image Processing: Algorithms and Systems XVII proceedings, 2019. – link
  • Wu, B. Xu, E. A. Bernal, R. L. Hill, E. B. Brown, and D. Desa “Breast Cancer Tissue Sub-Type Classification from Second Harmonic Generation Images via Machine Learning,” IEEE EMB Special Topic Conference on Healthcare Innovations and Point-of-Care Technologies, 2019.

2018:

  • J. A. Smith, J. C. Handley, and G. P. Dietl (2018). Effects of dams on downstream molluscan predator-prey interactions in the Colorado River estuary. Proceedings of the Royal Society B: Biological Sciences, 285(1879). – link.
  • J. A. Smith, J. C. Handley, and G. P. Dietl (2018). On drilling frequency and Manly’s alpha: Towards a null model for predator preference in paleoecology. Palaios, 33(2), pp. 61-68. – link.
  • Arko Barman, Wencheng Wu, Robert Loce, Aaron Burry, “Person Re-Identification Using Overhead View Fisheye Lens Cameras,” 2018 IEEE International Symposium on Technologies for Homeland Security, 2018. – link
  • C. Ivany, C. Pietsch, J. C. Handley, R. Lockwood, W. D. Allmon and J. A. Sessa (2018). Little lasting impact of the Paleocene-Eocene Thermal Maximum on shallow marine mollusk faunas, Science Advances, 4(9). – link
  • D. Mehta, X. Zhao, E. Bernal, D. Wales. The Loss Surface of XOR Artificial Neural Networks. Phys. Rev. E 97, May 2018. – link
  • E. Bernal, R. Loce. Video Analytics in the Compressed Domain. Encyclopedia of Image Processing, Taylor and Francis Group, 2018. – link
  • E. Bernal, X. Yang, Q. Li, J. Kumar, S. Madhvanath, R. Bala. Deep Temporal Multimodal Fusion for Medical Procedure Monitoring using Wearable Sensors. IEEE Transactions on Multimedia, Vol. 20(1), Jan. 2018. – link
  • Lei Lin, Zhengbing He, and Srinivas Peeta. “Predicting Station-level Hourly Demand in a Large-scale Bike-sharing Network: A Graph Convolutional Neural Network Approach.” Transportation Research Part C: Emerging Techniques 97 (2018): 258-276. – link
  • L. Lin, J. C. Handley, Y. Gu, L. Zhu, X. Wen and A. W. Sadek (2018). Quantifying uncertainty in short-term traffic prediction and its application to optimal staffing level plan development. Transportation Research – Part C, 92, pp. 323-348. – link.
  • J. Ning, V. Babich, J. C. Handley and J. Keppo (2018). Risk-aversion and B2B contracting under asymmetric information: Evidence from managed print services. Operations Research, 66(2), pp. 392-408. – link

2017:

  • E. Bernal, Q. Li. Tensorial Compressive Sensing of Jointly Sparse Matrices with Applications to Color Imaging, in Proc. 2017 IEEE International Conference on Image Processing (ICIP), Beijing, China, Sept. 2017. – link
  • Guilfoos, Todd, Dalton Kell, Andrew Boslett, and Elaine Hill. “The economic and health effects of the Elk River Chemical Spill.” American Journal of Agricultural Economics 100(2): 609-624. 2017. – link
  • Kosloski, G. Dietl and J. C. Handley (2017). Anatomy of a cline: dissecting anti-predatory adaptations in a marine gastropod along the U.S. Atlantic Coast. Ecography, 40(11), pp. 1285-1299. – link
  • Lei Zhu, Jeffrey Gonder, and Lei Lin. “Prediction of Individual Social-Demographic Role Based on Travel Behavior Variability Using Long-Term GPS Data.” Journal of Advanced Transportation, 2017. – link
  • X. Yang, E. Bernal, et al. Deep Multimodal Representation Learning from Temporal Data, in Proc. 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Honolulu, HI, June 2017. – link