Quan Tran

505 total citations
15 papers, 261 citations indexed

About

Quan Tran is a scholar working on Artificial Intelligence, Automotive Engineering and Computer Vision and Pattern Recognition. According to data from OpenAlex, Quan Tran has authored 15 papers receiving a total of 261 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Artificial Intelligence, 4 papers in Automotive Engineering and 4 papers in Computer Vision and Pattern Recognition. Recurrent topics in Quan Tran's work include Autonomous Vehicle Technology and Safety (4 papers), Bayesian Modeling and Causal Inference (2 papers) and Energy Load and Power Forecasting (2 papers). Quan Tran is often cited by papers focused on Autonomous Vehicle Technology and Safety (4 papers), Bayesian Modeling and Causal Inference (2 papers) and Energy Load and Power Forecasting (2 papers). Quan Tran collaborates with scholars based in United States, Germany and Vietnam. Quan Tran's co-authors include Lawrence Chung, Alan Yuille, Zhe Lin, Long Mai, Joydeep Mitra, Nga Nguyen, Jiuxiang Gu, Rajiv Jain, Benjamin Van Durme and Puneet Mathur and has published in prestigious journals such as Electric Power Systems Research, 2021 IEEE/CVF International Conference on Computer Vision (ICCV) and Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies.

In The Last Decade

Quan Tran

14 papers receiving 248 citations

Peers

Countries citing papers authored by Quan Tran

Since Specialization

Citations

This map shows the geographic impact of Quan Tran's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Quan Tran with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Quan Tran more than expected).

Fields of papers citing papers by Quan Tran

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Quan Tran. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Quan Tran. The network helps show where Quan Tran may publish in the future.

Co-authorship network of co-authors of Quan Tran

This figure shows the co-authorship network connecting the top 25 collaborators of Quan Tran. A scholar is included among the top collaborators of Quan Tran based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Quan Tran. Quan Tran is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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15 of 15 papers shown

#	Work	Indexed citations
1	Learning model combining convolutional deep neural network with a self-attention mechanism for AC optimal power flow 2024 ·Electric Power Systems Research ·Quan Tran, Joydeep Mitra, Nga Nguyen	7
2	Advanced convolutional neural network for optimizing AC power flow 2024 ·Quan Tran, Joydeep Mitra, Nga Nguyen	0
3	LayerDoc: Layer-wise Extraction of Spatial Hierarchical Structure in Visually-Rich Documents 2023 ·2023 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV) ·Puneet Mathur, Rajiv Jain, (unknown), Jiuxiang Gu, Franck Dernoncourt, (unknown), Quan Tran, (unknown), Ani Nenkova, Dinesh Manocha, Vlad I. Morariu	1
4	Multimodal Intent Discovery from Livestream Videos 2022 ·Adyasha Maharana, Quan Tran, Franck Dernoncourt, Seunghyun Yoon, Trung Bui, Walter Chang, Mohit Bansal	3
5	An Enhancement of Multi-objective Optimization Method in Unbalanced Power Distribution System Integrated Distributed Energy Resources 2022 ·Dinh Thanh Viet, Quan Tran	1
6	DocTime: A Document-level Temporal Dependency Graph Parser 2022 ·Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies ·Puneet Mathur, Vlad I. Morariu, (unknown), Jiuxiang Gu, Franck Dernoncourt, Quan Tran, Ani Nenkova, Dinesh Manocha, Rajiv Jain	5
7	Calibrating Concepts and Operations: Towards Symbolic Reasoning on Real Images 2021 ·2021 IEEE/CVF International Conference on Computer Vision (ICCV) ·(unknown), (unknown), Yixiao Zhang, Cihang Xie, Quan Tran, Benjamin Van Durme, Alan Yuille	9
8	Context-Aware Group Captioning via Self-Attention and Contrastive Features 2020 ·(unknown), Quan Tran, Long Mai, Zhe Lin, Alan Yuille	27
9	Electrochemical Upgrading of Bio-Oil 2016 ·ECS Meeting Abstracts ·Luis A. Diaz, Tedd E. Lister, Asanga B. Padmaperuma, Michael A. Lilga, Heather Job, Teresa Lemmon, Quan Tran	1
10	Online maneuver recognition and multimodal trajectory prediction for intersection assistance using non-parametric regression 2014 ·Quan Tran, (unknown)	124
11	Modelling of traffic situations at urban intersections with probabilistic non-parametric regression 2013 ·Quan Tran, (unknown)	34
12	A probabilistic discriminative approach for situation recognition in traffic scenarios 2012 ·Quan Tran, (unknown)	9
13	Probabilistic Maneuver Prediction in Traffic Scenarios. 2011 ·(unknown), Quan Tran	17
14	UNDERSTANDING OBJECT RELATIONS IN TRAFFIC SCENES 2010 ·(unknown), (unknown), (unknown), Quan Tran	3
15	NFR-Assistant: tool support for achieving quality 2003 ·Quan Tran, Lawrence Chung	20

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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