Dihua Wu

1.3k citations
16 papers · 1.0k indexed · 1 hit paper · h-index 12
Topics
Animal Behavior and Welfare Studies (7 papers)Food Supply Chain Traceability (6 papers)Effects of Environmental Stressors on Livestock (5 papers)
Partner nations
ChinaTunisia

In The Last Decade

Dihua Wu

16 papers receiving 973 citations

Hit Papers

Using channel pruning-based YOLO v4 deep learning algorit...20202026202220242020100200300

Peers

Dihua Wu
Comparison fields: 5 of 114
  • Plant Science 356
  • Small Animals 262
  • Animal Science and Zoology 234
  • Computer Vision and Pattern Recognition 191
  • Food Science 185
Replace Leifeng Guo with:
Leifeng Guo China
Hao Guo China
Deqin Xiao China
Yueju Xue China
Yongliang Qiao China
Weizheng Shen China
Abozar Nasirahmadi Germany
Lilong Chai United States
Shuqin Tu China
Huaibo Song China
Dihua Wu relative to Leifeng Guo China Leifeng Guo's profile →
Citations per field
00.5×1.5×1.9×
Leifeng Guo · 1×
Citations per year

Countries citing papers authored by Dihua Wu

Since Specialization
Citations

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

Fields of papers citing papers by Dihua Wu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Dihua Wu

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

All Works

16 of 16 papers shown
#WorkIndexed citations
1 4
2 2
3 5
4 10
5 24
6 13
7 44
8 82
9 32
10 84
11 44
12
Using channel pruning-based YOLO v4 deep learning algorithm for the real-time and accurate detection of apple flowers in natural environmentsbreakdown →
374
13 73
14 12
15 115
16 86

About Dihua Wu

Dihua Wu is a scholar working on Animal Science and Zoology, Small Animals and Food Science, having authored 16 papers that have together received 1.0k indexed citations. Recurring topics across this work include Animal Behavior and Welfare Studies (7 papers), Food Supply Chain Traceability (6 papers) and Effects of Environmental Stressors on Livestock (5 papers). The work is most often cited by research in Small Animals (262 citations), Animal Science and Zoology (234 citations) and Food Science (185 citations). Dihua Wu has collaborated with scholars based in China and Tunisia. Frequent co-authors include Huaibo Song, Mei Jiang, Bo Jiang, Yibin Ying, Mingchuan Zhou, Di Cui, Qian Wu, Dongjian He, Lei Song and Han Wang. Their work appears in journals such as IEEE Access, Journal of Dairy Science and Computers and Electronics in Agriculture.

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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