Guozhong Dai

2.0k citations
124 papers · 1.3k indexed · h-index 16
Topics
Interactive and Immersive Displays (28 papers)Hand Gesture Recognition Systems (18 papers)Tactile and Sensory Interactions (14 papers)
Partner nations
ChinaUnited StatesJapan

In The Last Decade

Guozhong Dai

110 papers receiving 1.2k citations

Peers

Guozhong Dai
Comparison fields: 5 of 125
  • Computer Vision and Pattern Recognition 424
  • Human-Computer Interaction 404
  • Civil and Structural Engineering 268
  • Cognitive Neuroscience 159
  • Materials Chemistry 129
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Citations per field
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Citations per year

Countries citing papers authored by Guozhong Dai

Since Specialization
Citations

This map shows the geographic impact of Guozhong Dai'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 Guozhong Dai with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Guozhong Dai more than expected).

Fields of papers citing papers by Guozhong Dai

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Guozhong Dai. 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 Guozhong Dai. The network helps show where Guozhong Dai may publish in the future.

Co-authorship network of co-authors of Guozhong Dai

This figure shows the co-authorship network connecting the top 25 collaborators of Guozhong Dai. A scholar is included among the top collaborators of Guozhong Dai 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 Guozhong Dai. Guozhong Dai is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 1
2 2
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ニューラル計算に基づくマルチモーダル相互作用モデリングの予備的研究【Powered by NICT】
1
4
Personalized Interaction Techniques of Vision-Based 3D Dynamic Gestures Based on Small Sample Learning
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5 7
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Ubiquitous human-computer interaction in cloud manufacturing
9
7
Test and research of vertical anti-seepage slurry for domestic waste landfill site
1
8 1
9 6
10 46
11
Topic Analysis of Chinese Text Based on Small World Model
2
12
Evolution of the Human-computer Interaction
2
13 14
14
Fast-Speeding Navigation: Combining Walking with Flying
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15
A Kind of Distributed Control System for Wireless Transceiver Base Stations
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16 6
17 4
18 2
19 0
20
The Efficiency of Various Multimodal Input Interfaces Evaluated in Two Empirical Studies
1

About Guozhong Dai

Guozhong Dai is a scholar working on Human-Computer Interaction, Computer Graphics and Computer-Aided Design and Computer Vision and Pattern Recognition, having authored 124 papers that have together received 1.3k indexed citations. Recurring topics across this work include Interactive and Immersive Displays (28 papers), Hand Gesture Recognition Systems (18 papers) and Tactile and Sensory Interactions (14 papers). The work is most often cited by research in Human-Computer Interaction (404 citations), Computer Vision and Pattern Recognition (424 citations) and Civil and Structural Engineering (268 citations). Guozhong Dai has collaborated with scholars based in China, United States and Japan. Frequent co-authors include Hongan Wang, Feng Tian, Yang Song, Li Zhao, Luguang Song, Jin Huang, Yang Li, Jiaping Liu, Xinli Guo and Weixin Wang. Their work appears in journals such as Construction and Building Materials, Computers in Human Behavior and Pattern Recognition.

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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