2024
H. Vakharia and X. Du, “Bi-capacity Choquet Integral for Sensor Fusion with Label Uncertainty”, Accepted.
2023
P. Stratton and X. Du, “MIC-AQT: Improving Domain Adaptive Object Detection of Adversarial Query Transformers with Masked Image Consistency“, IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Oct. 2023. Oral Presentation. [Poster]
S. Varaganti, A.M. Kanu-Asiegbu, and X. Du, “Temporal CFT: Multi-Temporal Cross-Modality Fusion Transformer for Multispectral Video Object Detection“, IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Oct. 2023. Poster Presentation. [Poster]
H.Vakharia and X. Du, “Efficient Multi-Resolution Fusion for Remote Sensing Data with Label Uncertainty“, International Geoscience and Remote Sensing Symposium (IGARSS), July 2023.
2022
A. M. Kanu-Asiegbu, R. Vasudevan, and X. Du, “BiPOCO: Bi-Directional Trajectory Prediction with Pose Constraints for Pedestrian Anomaly Detection,” 39th International Conference on Machine Learning (ICML 2022) Safe Learning for Autonomous Driving (SL4AD) Workshop, July 2022.
2021
A. M. Kanu-Asiegbu, R. Vasudevan, and X. Du, “Leveraging Trajectory Prediction for Pedestrian Video Anomaly Detection,” IEEE Symposium Series on Computational Intelligence, Dec. 2021, pp. 01-08.
Y. Yao, E. Atkins, M. Johnson-Roberson, R. Vasudevan, and X. Du, “Coupling Intent and Action for Pedestrian Crossing Behavior Prediction“, in 30th International Joint Conference on Artificial Intelligence (IJCAI-21), pp. 1238-1244, Aug. 2021.
X. Du, N. Pusalkar, R. Vasudevan, and M. Johnson-Roberson, “Angle-Regulated Transformer Network for Pedestrian Trajectory Prediction,” in 30th International Joint Conference on Artificial Intelligence Artificial Intelligence for Autonomous Driving (IJCAI-21 AI4AD) Workshop, Aug. 2021.
Y. Yao, E. Atkins, M. Johnson-Roberson, R. Vasudevan, and X. Du, “BiTraP: Bi-directional Pedestrian Trajectory Prediction with Multi-modal Goal Estimation“, in IEEE Robotics and Automation Letters, vol. 6, no. 2, pp. 1463-1470, April 2021.
2020
[Book Chapter] C. Jiao, X. Du, and A. Zare, “Addressing the Inevitable Imprecision: Multiple Instance Learning for Hyperspectral Image Analysis”, in Hyperspectral Image Analysis, pp. 141-185, Springer, Cham, 2020. Prasad, S. and Chanussot, J. (Eds.)
X. Du, R. Vasudevan, and M. Johnson-Roberson, “Unsupervised Pedestrian Pose Prediction: A Deep Predictive Coding Network-Based Approach for Autonomous Vehicle Perception,” in IEEE Robotics and Automation Magazine, vol. 27, no. 2, pp. 129-138, June 2020.
F. Bu, T. Le, X. Du, R. Vasudevan, and M. Johnson-Roberson, “Pedestrian Planar LiDAR Pose (PPLP) Network for Oriented Pedestrian Detection Based on Planar LiDAR and Monocular Images,” in IEEE Robotics and Automation Letters, vol. 5, no. 2, pp. 1626-1633, April 2020.
X. Du and A. Zare, “Multiresolution Multimodal Sensor Fusion For Remote Sensing Data With Label Uncertainty,” IEEE Transactions on Geoscience and Remote Sensing, vol. 58, no. 4, pp. 2755-2769, April 2020.
2019
X. Du, A. Zare and D. Anderson, “Multiple Instance Choquet Integral with Binary Fuzzy Measures for Remote Sensing Classifier Fusion with Imprecise Labels,” IEEE Symposium Series on Computational Intelligence, 2019, pp. 1154-1162.
C. Anderson, X. Du, R. Vasudevan and M. Johnson-Roberson, “Stochastic Sampling Simulation for Pedestrian Trajectory Prediction,” IEEE/RSJ International Conference on Intelligent Robots and Systems, Macau, China, 2019, pp. 4236-4243.
X. Du, R. Vasudevan and M. Johnson-Roberson, “Bio-LSTM: A Biomechanically Inspired Recurrent Neural Network for 3-D Pedestrian Pose and Gait Prediction,” IEEE Robotics and Automation Letters, vol. 4, no. 2, pp. 1501-1508, April 2019.
X. Du and A. Zare, “Multiple Instance Choquet Integral Classifier Fusion and Regression for Remote Sensing Applications,” IEEE Transactions on Geoscience and Remote Sensing, vol. 57, no. 5, pp. 2741-2753, May 2019.
2018
M. A. Islam, D. T. Anderson, X. Du, T. C. Havens, and C. Wagner, “Efficient Binary Fuzzy Measure Representation and Choquet Integral Learning,” in Int. Conf. Information Processing and Management of Uncertainty in Knowledge-Based Systems, Cádiz, Spain, 2018, pp. 115-126.
2017
X. Du, “Multiple Instance Choquet Integral For Multi-Resolution Sensor Fusion,” Ph.D. dissertation, University of Missouri, Columbia, MO, 2017.
X. Du, A. Seethepalli, H. Sun, A. Zare, and J. T. Cobb, “Environmentally-Adaptive Target Recognition for SAS Imagery,” in Proc. SPIE 10182, Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XXII, Anaheim, CA, 2017, pp. 1-15.
J. T. Cobb, X. Du, A. Zare, and M. Emigh, “Multiple-instance Learning-based Sonar Image Classification,” in Proc. SPIE 10182, Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XXII, Anaheim, CA, 2017, pp. 1-8.
X. Du and A. Zare, “Technical Report: Scene Label Ground Truth Map for MUUFL Gulfport Data Set,” University of Florida, Gainesville, FL, Tech. Rep. 20170417, 2017.
2016
X. Du, A. Zare, J. Keller, and D. Anderson, “Multiple Instance Choquet Integral for Classifier Fusion,” in IEEE Congress on Evolutionary Computation (CEC), Vancouver, BC, 2016, pp. 1054-1061.
2015
X. Du, A. Zare, and J. T. Cobb, “Possibilistic context identification for SAS imagery,” in Proc. SPIE 9454, Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XX, Baltimore, MD, 2015, pp. 1-11.
2014
X. Du, A. Zare, P. Gader, and D. Dranishnikov, “Spatial and Spectral Unmixing Using the Beta Compositional Model,” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (J-STARS), vol. 7, pp. 1994-2003, 2014.
2013
X. Du, “Accounting for Spectral Variability in Hyperspectral Unmixing Using Beta Endmember Distribution,” M.S. thesis, University of Missouri, Columbia, MO, 2013.