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08/29/2023
A Comparative Study of Loss Functions: Traffic Predictions in Regular and Congestion Scenarios
Spatiotemporal graph neural networks have achieved state-of-the-art perf...
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02/03/2023
Analyzing the impact of climate change on critical infrastructure from the scientific literature: A weakly supervised NLP approach
Natural language processing (NLP) is a promising approach for analyzing ...
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09/27/2022
Explainable Graph Pyramid Autoformer for Long-Term Traffic Forecasting
Accurate traffic forecasting is vital to an intelligent transportation s...
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04/04/2022
Deep-Ensemble-Based Uncertainty Quantification in Spatiotemporal Graph Neural Networks for Traffic Forecasting
Deep-learning-based data-driven forecasting methods have produced impres...
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12/17/2021
A data-centric weak supervised learning for highway traffic incident detection
Using the data from loop detector sensors for near-real-time detection o...
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08/28/2020
Dynamic Graph Neural Network for Traffic Forecasting in Wide Area Networks
Wide area networking infrastructures (WANs), particularly science and re...
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04/24/2020
Bharatanatyam Dance Transcription using Multimedia Ontology and Machine Learning
Indian Classical Dance is an over 5000 years' old multi-modal language f...
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04/17/2020
Beat Detection and Automatic Annotation of the Music of Bharatanatyam Dance using Speech Recognition Techniques
Bharatanatyam, an Indian Classical Dance form, represents the rich cultu...
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04/17/2020
Transfer Learning with Graph Neural Networks for Short-Term Highway Traffic Forecasting
Highway traffic modeling and forecasting approaches are critical for int...
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09/24/2019
Graph-Partitioning-Based Diffusion Convolution Recurrent Neural Network for Large-Scale Traffic Forecasting
Traffic forecasting approaches are critical to developing adaptive strat...
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09/24/2019