Search Results for author: Shih-Yuan Yu

Found 5 papers, 3 papers with code

Graph Learning for Cognitive Digital Twins in Manufacturing Systems

no code implementations17 Sep 2021 Trier Mortlock, Deepan Muthirayan, Shih-Yuan Yu, Pramod P. Khargonekar, Mohammad A. Al Faruque

In this paper, we detail the cognitive digital twin as the next stage of advancement of a digital twin that will help realize the vision of Industry 4. 0.

Graph Learning

roadscene2vec: A Tool for Extracting and Embedding Road Scene-Graphs

1 code implementation2 Sep 2021 Arnav Vaibhav Malawade, Shih-Yuan Yu, Brandon Hsu, Harsimrat Kaeley, Anurag Karra, Mohammad Abdullah Al Faruque

The goal of roadscene2vec is to enable research into the applications and capabilities of road scene-graphs by providing tools for generating scene-graphs, graph learning models to generate spatio-temporal scene-graph embeddings, and tools for visualizing and analyzing scene-graph-based methodologies.

Action Classification Graph Embedding +4

HW2VEC: A Graph Learning Tool for Automating Hardware Security

1 code implementation26 Jul 2021 Shih-Yuan Yu, Rozhin Yasaei, Qingrong Zhou, Tommy Nguyen, Mohammad Abdullah Al Faruque

To attract more attention, we propose HW2VEC, an open-source graph learning tool that lowers the threshold for newcomers to research hardware security applications with graphs.

Graph Learning

GNN4IP: Graph Neural Network for Hardware Intellectual Property Piracy Detection

no code implementations19 Jul 2021 Rozhin Yasaei, Shih-Yuan Yu, Emad Kasaeyan Naeini, Mohammad Abdullah Al Faruque

In this work, we propose a novel methodology, GNN4IP, to assess similarities between circuits and detect IP piracy.

Scene-Graph Augmented Data-Driven Risk Assessment of Autonomous Vehicle Decisions

3 code implementations31 Aug 2020 Shih-Yuan Yu, Arnav V. Malawade, Deepan Muthirayan, Pramod P. Khargonekar, Mohammad A. Al Faruque

Finally, we demonstrate that the use of spatial and temporal attention layers improves our model's performance by 2. 7% and 0. 7% respectively, and increases its explainability.

Autonomous Driving Scene Classification

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