Hidehisa Nakayama

31 papers receiving 941 citations

Peers

Hidehisa Nakayama
Comparison fields: 5 of 52
  • Computer Networks and Communications 1.0k
  • Electrical and Electronic Engineering 529
  • Artificial Intelligence 71
  • Computer Vision and Pattern Recognition 49
  • Aerospace Engineering 41
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Guido R. Hiertz Germany
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Borhanuddin Mohd Ali Malaysia
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Citations per field
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Citations per year

Countries citing papers authored by Hidehisa Nakayama

Since Specialization
Citations

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

Fields of papers citing papers by Hidehisa Nakayama

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Hidehisa Nakayama

This figure shows the co-authorship network connecting the top 25 collaborators of Hidehisa Nakayama. A scholar is included among the top collaborators of Hidehisa Nakayama 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 Hidehisa Nakayama. Hidehisa Nakayama 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 59
2 4
3 5
4 69
5
A Study of Definition of Traffic Pattern on Traitor Tracing Technology
1
6 1
7 16
8 5
9 25
10 93
11
Detecting Blackhole Attack on AODV-based Mobile Ad Hoc Networks by Dynamic Learning Method.
258
12 334
13 3
14 20
15
A SURVEY OF ROUTING ATTACKS IN MOBILE AD HOC NETWORKS S ECURITY I N W IRELESS M OBILE A D H OC A ND S ENSOR N ETWORKS
6
16
Detecting Blackhole Attack on AODV-based Mobile Ad Hoc Networksby Dynamic learning method
5
17 41
18 1
19 3
20 14

About Hidehisa Nakayama

Hidehisa Nakayama is a scholar working on Computer Networks and Communications, Computer Vision and Pattern Recognition and Electrical and Electronic Engineering, having authored 31 papers that have together received 1.1k indexed citations. Recurring topics across this work include Mobile Ad Hoc Networks (20 papers), Opportunistic and Delay-Tolerant Networks (9 papers) and Vehicular Ad Hoc Networks (VANETs) (8 papers). The work is most often cited by research in Computer Networks and Communications (1.0k citations), Electrical and Electronic Engineering (529 citations) and Signal Processing (31 citations). Hidehisa Nakayama has collaborated with scholars based in Japan, Australia and United States. Frequent co-authors include Nei Kato, Abbas Jamalipour, Bounpadith Kannhavong, Yoshiaki Nemoto, Satoshi Kurosawa, Yoshiaki Nemoto, Nirwan Ansari, Y. Nemoto, Zubair Md. Fadlullah and Xuemin Shen. Their work appears in journals such as IEEE Transactions on Automatic Control, IEEE Transactions on Wireless Communications and IEEE Transactions on Vehicular Technology.

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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