Hao Dong

1.1k citations
23 papers · 633 indexed · 1 hit paper · h-index 9
Co-authors
Jing YangJun WangShanghang ZhangShaobo LiZheng WangZihan DingShihao TangTong Zhang
Topics
Advanced Image and Video Retrieval Techniques (5 papers)3D Shape Modeling and Analysis (5 papers)Robot Manipulation and Learning (4 papers)

In The Last Decade

Hao Dong

22 papers receiving 609 citations

Hit Papers

Using Deep Learning to Detect Defects in Manufacturing: A...2020202620222024202050100150200250

Peers

Hao Dong
Comparison fields: 5 of 98
  • Industrial and Manufacturing Engineering 196
  • Computer Vision and Pattern Recognition 164
  • Mechanical Engineering 103
  • Artificial Intelligence 100
  • Control and Systems Engineering 87
Replace Jinan Gu with:
Jinan Gu China
Yaguang Kong China
Giuseppe Acciani Italy
Rômulo Gonçalves Lins Brazil
Weidong Cao China
Shubin Zheng China
R.M. Parkin United Kingdom
Víctor Ayala-Ramírez Mexico
Hao Dong relative to Jinan Gu China Jinan Gu's profile →
Citations per field
00.5×1.5×
Jinan Gu · 1×
Citations per year

Countries citing papers authored by Hao Dong

Since Specialization
Citations

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

Fields of papers citing papers by Hao Dong

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Hao Dong

This figure shows the co-authorship network connecting the top 25 collaborators of Hao Dong. A scholar is included among the top collaborators of Hao Dong 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 Hao Dong. Hao Dong 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 9
3 2
4 4
5 4
6 11
7 32
8 28
9 1
10 4
11 31
12 1
13 2
14
Generative 3D Part Assembly via Dynamic Graph Learning
4
15
Using Deep Learning to Detect Defects in Manufacturing: A Comprehensive Survey and Current Challengesbreakdown →
297
16 148
17 2
18 2
19 0
20
The design of embedded SD card memory
1

About Hao Dong

Hao Dong is a scholar working on Computer Vision and Pattern Recognition, Computer Graphics and Computer-Aided Design and Industrial and Manufacturing Engineering, having authored 23 papers that have together received 633 indexed citations. Recurring topics across this work include Advanced Image and Video Retrieval Techniques (5 papers), 3D Shape Modeling and Analysis (5 papers) and Robot Manipulation and Learning (4 papers). The work is most often cited by research in Industrial and Manufacturing Engineering (196 citations), Computer Vision and Pattern Recognition (164 citations) and Media Technology (57 citations). Hao Dong has collaborated with scholars based in China, United States and Hong Kong. Frequent co-authors include Jing Yang, Jun Wang, Shanghang Zhang, Shaobo Li, Zheng Wang, Zihan Ding, Shihao Tang, Tong Zhang, Yin Zhuang and He Chen. Their work appears in journals such as Remote Sensing, Neurocomputing and Materials.

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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