Ruohan Zong
Orcid: 0000-0002-6499-3406
According to our database1,
Ruohan Zong
authored at least 21 papers
between 2019 and 2024.
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Bibliography
2024
SymLearn: A Symbiotic Crowd-AI Collective Learning Framework to Web-based Healthcare Policy Adherence Assessment.
Proceedings of the ACM on Web Conference 2024, 2024
MMAdapt: A Knowledge-guided Multi-source Multi-class Domain Adaptive Framework for Early Health Misinformation Detection.
Proceedings of the ACM on Web Conference 2024, 2024
2023
A crowd-AI dynamic neural network hyperparameter optimization approach for image-driven social sensing applications.
Knowl. Based Syst., October, 2023
ContrastFaux: Sparse Semi-supervised Fauxtography Detection on the Web using Multi-view Contrastive Learning.
Proceedings of the ACM Web Conference 2023, 2023
CollabEquality: A Crowd-AI Collaborative Learning Framework to Address Class-wise Inequality in Web-based Disaster Response.
Proceedings of the ACM Web Conference 2023, 2023
A Crowdsourced Learning Framework to Optimize Cross-Event QoS in AI-powered Social Sensing.
Proceedings of the 20th Annual IEEE International Conference on Sensing, 2023
On Optimizing Model Generality in AI-based Disaster Damage Assessment: A Subjective Logic-driven Crowd-AI Hybrid Learning Approach.
Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023
2022
On Coupling Classification and Super-Resolution in Remote Urban Sensing: An Integrated Deep Learning Approach.
IEEE Trans. Geosci. Remote. Sens., 2022
CollabLearn: An Uncertainty-Aware Crowd-AI Collaboration System for Cultural Heritage Damage Assessment.
IEEE Trans. Comput. Soc. Syst., 2022
CrowdOptim: A Crowd-driven Neural Network Hyperparameter Optimization Approach to AI-based Smart Urban Sensing.
Proc. ACM Hum. Comput. Interact., 2022
CrowdNAS: A Crowd-guided Neural Architecture Searching Approach to Disaster Damage Assessment.
Proc. ACM Hum. Comput. Interact., 2022
An active one-shot learning approach to recognizing land usage from class-wise sparse satellite imagery in smart urban sensing.
Knowl. Based Syst., 2022
On streaming disaster damage assessment in social sensing: A crowd-driven dynamic neural architecture searching approach.
Knowl. Based Syst., 2022
2021
SuperClass: A Deep Duo-Task Learning Approach to Improving QoS in Image-driven Smart Urban Sensing Applications.
Proceedings of the 29th IEEE/ACM International Symposium on Quality of Service, 2021
A Crowd-driven Dynamic Neural Architecture Searching Approach to Quality-aware Streaming Disaster Damage Assessment.
Proceedings of the 29th IEEE/ACM International Symposium on Quality of Service, 2021
StreamCollab: A Streaming Crowd-AI Collaborative System to Smart Urban Infrastructure Monitoring in Social Sensing.
Proceedings of the Ninth AAAI Conference on Human Computation and Crowdsourcing, 2021
A deep contrastive learning approach to extremely-sparse disaster damage assessment in social sensing.
Proceedings of the ASONAM '21: International Conference on Advances in Social Networks Analysis and Mining, Virtual Event, The Netherlands, November 8, 2021
2020
TransRes: A Deep Transfer Learning Approach to Migratable Image Super-Resolution in Remote Urban Sensing.
Proceedings of the 17th Annual IEEE International Conference on Sensing, 2020
On Privileged Information Driven Robust Face Verification: A Siamese Convolutional Neural Network Approach.
Proceedings of the 2020 IEEE International Conference on Big Data (IEEE BigData 2020), 2020
A Hybrid Transfer Learning Approach to Migratable Disaster Assessment in Social Media Sensing.
Proceedings of the IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, 2020
2019
TransLand: An Adversarial Transfer Learning Approach for Migratable Urban Land Usage Classification using Remote Sensing.
Proceedings of the 2019 IEEE International Conference on Big Data (IEEE BigData), 2019