Wenwen Ding

Orcid: 0000-0001-8582-2078

According to our database1, Wenwen Ding authored at least 29 papers between 2015 and 2024.

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Bibliography

2024
The Ripple of Technology: A Literature Review on Examining the Impact of ICT on Tibetan Refugees Through the Lens of Modernity and Postmodernism.
Proceedings of the 57th Hawaii International Conference on System Sciences, 2024

Parallel Treasury for TRUE DAOs: Model, Indicators and Mechanism<sup>*</sup>.
Proceedings of the Australian & New Zealand Control Conference, 2024

2023
A New Architecture and Mechanism for Decentralized Science MetaMarkets.
IEEE Trans. Syst. Man Cybern. Syst., September, 2023

A Novel Approach for Predictable Governance of Decentralized Autonomous Organizations Based on Parallel Intelligence.
IEEE Trans. Syst. Man Cybern. Syst., May, 2023

Web3-Based Decentralized Autonomous Organizations and Operations: Architectures, Models, and Mechanisms.
IEEE Trans. Syst. Man Cybern. Syst., April, 2023

DAO to HANOI via DeSci: AI Paradigm Shifts from AlphaGo to ChatGPT.
IEEE CAA J. Autom. Sinica, April, 2023

AI4S Based on DeSci: Reference Model and Research Issues.
Proceedings of the IEEE International Conference on Systems, Man, and Cybernetics, 2023

TAO-Based Data Governance in Intelligent Transportation Systems.
Proceedings of the 25th IEEE International Conference on Intelligent Transportation Systems, 2023

SensorDAO: A New Framework of Sensor Governance for Internet of Vehicles.
Proceedings of the IEEE 3rd International Conference on Digital Twins and Parallel Intelligence, 2023

2022
Parallel Philosophy for MetaOrganizations With MetaOperations: From Leibniz's Monad to HanoiDAO.
IEEE Trans. Comput. Soc. Syst., 2022

DeSci Based on Web3 and DAO: A Comprehensive Overview and Reference Model.
IEEE Trans. Comput. Soc. Syst., 2022

Graph-based relational reasoning in a latent space for skeleton-based action recognition.
J. Vis. Commun. Image Represent., 2022

The DAO to DeSci: AI for Free, Fair, and Responsibility Sensitive Sciences.
IEEE Intell. Syst., 2022

Temporal segment graph convolutional networks for skeleton-based action recognition.
Eng. Appl. Artif. Intell., 2022

2021
A New Method for Mapping Active Joint Locations of Skeletons to Pre-Shape Space for Action Recognition.
Int. J. Pattern Recognit. Artif. Intell., 2021

Skeleton-Based Square Grid for Human Action Recognition With 3D Convolutional Neural Network.
IEEE Access, 2021

Parallel Governance for Decentralized Autonomous Organizations enabled by Blockchain and Smart Contracts.
Proceedings of the IEEE 2nd International Conference on Digital Twins and Parallel Intelligence, 2021

2020
Global relational reasoning with spatial temporal graph interaction networks for skeleton-based action recognition.
Signal Process. Image Commun., 2020

2019
Decentralized Autonomous Organizations: Concept, Model, and Applications.
IEEE Trans. Comput. Soc. Syst., 2019

2018
Tensor-based linear dynamical systems for action recognition from 3D skeletons.
Pattern Recognit., 2018

Human action recognition using similarity degree between postures and spectral learning.
IET Comput. Vis., 2018

2017
Learning Linear Dynamical Systems with High-Order Tensor Data for Skeleton based Action Recognition.
CoRR, 2017

A systematic review of studies on predicting student learning outcomes using learning analytics.
Proceedings of the Seventh International Learning Analytics & Knowledge Conference, 2017

2016
Profile HMMs for skeleton-based human action recognition.
Signal Process. Image Commun., 2016

Learning hierarchical spatio-temporal pattern for human activity prediction.
J. Vis. Commun. Image Represent., 2016

Human action recognition using spectral embedding to similarity degree between postures.
Proceedings of the 2016 Visual Communications and Image Processing, 2016

2015
Weak label for fast online visual tracking.
Signal Process. Image Commun., 2015

STFC: Spatio-temporal feature chain for skeleton-based human action recognition.
J. Vis. Commun. Image Represent., 2015

Skeleton-Based Human Action Recognition with Profile Hidden Markov Models.
Proceedings of the Computer Vision - CCF Chinese Conference, 2015


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