Jiangtao Huang

Orcid: 0009-0003-0846-5099

According to our database1, Jiangtao Huang authored at least 14 papers between 2014 and 2024.

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Bibliography

2024
An three-in-one on-demand ride-hailing prediction model based on multi-agent reinforcement learning.
Appl. Soft Comput., December, 2024

A three-in-one dynamic shared bicycle demand forecasting model under non-classical conditions.
Appl. Intell., September, 2024

DMF-Net: Image-Guided Point Cloud Completion with Dual-Channel Modality Fusion and Shape-Aware Upsampling Transformer.
CoRR, 2024

Knowledge Graph Relation Patterns Networks for Recommendations.
Proceedings of the Web Information Systems Engineering - WISE 2024, 2024

2023
RDD-net: Robust duplicated-diffusion watermarking based on deep network.
J. Vis. Commun. Image Represent., October, 2023

ARWGAN: Attention-Guided Robust Image Watermarking Model Based on GAN.
IEEE Trans. Instrum. Meas., 2023

Benchmarking Software Vulnerability Detection Techniques: A Survey.
CoRR, 2023

Enhancing the Performance of Automated Grade Prediction in MOOC using Graph Representation Learning.
Proceedings of the 10th IEEE International Conference on Data Science and Advanced Analytics, 2023

A Mix-up Strategy to Enhance Adversarial Training with Imbalanced Data.
Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023

2021
A Novel HDR Image Zero-Watermarking Based on Shift-Invariant Shearlet Transform.
Secur. Commun. Networks, 2021

Attention-Based Deep Multi-scale Network for Plant Leaf Recognition.
Proceedings of the Intelligent Computing Theories and Application, 2021

Automatic Identification of Teachers in Social Media using Positive Unlabeled Learning.
Proceedings of the 2021 IEEE International Conference on Big Data (Big Data), 2021

2020
Online Academic Course Performance Prediction using Relational Graph Convolutional Neural Network.
Proceedings of the 13th International Conference on Educational Data Mining, 2020

2014
An improved Gene Expression Programming approach for symbolic regression problems.
Neurocomputing, 2014


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