Takashi Chikayama

42 papers receiving 365 citations

Peers

Takashi Chikayama
Comparison fields: 5 of 52
  • Artificial Intelligence 291
  • Computer Networks and Communications 123
  • Hardware and Architecture 96
  • Computational Theory and Mathematics 60
  • Computer Vision and Pattern Recognition 56
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Countries citing papers authored by Takashi Chikayama

Since Specialization
Citations

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

Fields of papers citing papers by Takashi Chikayama

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Takashi Chikayama

This figure shows the co-authorship network connecting the top 25 collaborators of Takashi Chikayama. A scholar is included among the top collaborators of Takashi Chikayama 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 Takashi Chikayama. Takashi Chikayama 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
UTTime: Temporal Relation Classification using Deep Syntactic Features
31
2
Robust Generation of Dynamical Patterns in Human Motion by a Deep Belief Nets
8
3
Classification precision of several candidate using multiclass support vector machine in generic object recognition
3
4
MPI/GXP: An Adaptive Message Passing System for Wide-Area Environments
1
5
Estimating reliability of the rules in decision lists using Bayesian learning
1
6
The Fifth Generation Project: Personal Perspectives.
6
7
The Design of the PIMOS File System.
2
8
Operating System PIMOS and Kernel Language KL1
8
9 1
10
Lazy Reference Counting: An Incremental Garbage Collection Method for Parallel Inference Machines.
9
11
Macro Processing in Prolog.
1
12
Macro-Call Instruction for the Efficient KL1 Implementation on PIM.
1
13
Parallel Inference System Researches in the FGCS Project.
1
14
Multiple Reference Management in Flat GHC.
21
15
An Abstract KL1 Machine and Its Instruction Set.
19
16
A Sequential Implementation of Concurrent Prolog Based on the Shallow Binding Scheme.
6
17
CONCURRENT PROLOG COMPILER ON TOP OF PROLOG.
5
18
EFFICIENT STREAM/ARRAY PROCESSING IN LOGIC PROGRAMMING LANGUAGES.
5
19
Overall design of SIMPOS.
4
20
Unique Features of ESP.
11

About Takashi Chikayama

Takashi Chikayama is a scholar working on Hardware and Architecture, Computer Networks and Communications and Artificial Intelligence, having authored 49 papers that have together received 430 indexed citations. Recurring topics across this work include Parallel Computing and Optimization Techniques (12 papers), Distributed and Parallel Computing Systems (10 papers) and Topic Modeling (5 papers). The work is most often cited by research in Hardware and Architecture (96 citations), Artificial Intelligence (291 citations) and Computer Networks and Communications (123 citations). Takashi Chikayama has collaborated with scholars based in Japan, United Kingdom and United States. Frequent co-authors include Yoshimasa Tsuruoka, Makoto Miwa, Yasunori Kimura, Kazuma Hashimoto, Kenjiro Taura, Kazunori Ueda, Hiroshi Nakashima, Sampo Pyysalo, Masahiro Yamamoto and Hubert Soyer. Their work appears in journals such as Communications of the ACM, BMC Bioinformatics and Future Generation Computer Systems.

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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