Dauw, M.
* 1992: Omnifont recognition of text using topological recognition techniques
Dauwels, J.
* 2014: Spatiotemporal Patterns in Large-Scale Traffic Speed Prediction
* 2015: Low-Dimensional Models for Compressed Sensing and Prediction of Large-Scale Traffic Data
* 2015: Near-Lossless Compression for Large Traffic Networks
* 2016: Matrix and Tensor Based Methods for Missing Data Estimation in Large Traffic Networks
* 2016: On Centralized and Decentralized Architectures for Traffic Applications
* 2019: Action-Stage Emphasized Spatiotemporal VLAD for Video Action Recognition
* 2019: Dynamic Prediction of the Incident Duration Using Adaptive Feature Set
* 2019: Semantic Cues Enhanced Multimodality Multistream CNN for Action Recognition
* 2020: Estimating Travel Time Distributions by Bayesian Network Inference
* 2021: Context Model for Pedestrian Intention Prediction Using Factored Latent-Dynamic Conditional Random Fields
* 2021: Generic GPU-Accelerated Framework for the Dial-A-Ride Problem, A
* 2021: R3L: Connecting Deep Reinforcement Learning To Recurrent Neural Networks for Image Denoising Via Residual Recovery
* 2022: Factored Latent-Dynamic Conditional Random Fields for single and multi-label sequence modeling
* 2023: Efficient Variational Bayes Learning of Graphical Models With Smooth Structural Changes
* 2023: Learning to Solve Multiple-TSP With Time Window and Rejections via Deep Reinforcement Learning
* 2024: PEM: Perception Error Model for Virtual Testing of Autonomous Vehicles
Includes: Dauwels, J. Dauwels, J.[Justin]
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