Takeshi Koshiba

1.7k total citations
63 papers, 762 citations indexed

About

Takeshi Koshiba is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Computer Networks and Communications. According to data from OpenAlex, Takeshi Koshiba has authored 63 papers receiving a total of 762 indexed citations (citations by other indexed papers that have themselves been cited), including 43 papers in Artificial Intelligence, 17 papers in Computer Vision and Pattern Recognition and 13 papers in Computer Networks and Communications. Recurrent topics in Takeshi Koshiba's work include Cryptography and Data Security (25 papers), Chaos-based Image/Signal Encryption (9 papers) and Complexity and Algorithms in Graphs (8 papers). Takeshi Koshiba is often cited by papers focused on Cryptography and Data Security (25 papers), Chaos-based Image/Signal Encryption (9 papers) and Complexity and Algorithms in Graphs (8 papers). Takeshi Koshiba collaborates with scholars based in Japan, Bangladesh and United States. Takeshi Koshiba's co-authors include Pranab Kumar Dhar, Kaushik Deb, Behrouz Zolfaghari, Jun Kogure, Takeshi Shimoyama, Tomoyuki Morimae, Masaya Yasuda, Kazuhiro Yokoyama, Mohammad Shamsul Arefin and Md. Kowsher and has published in prestigious journals such as Scientific Reports, IEEE Transactions on Information Theory and Physical Review A.

In The Last Decade

Takeshi Koshiba

59 papers receiving 729 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Takeshi Koshiba Japan	16	384	213	110	101	91	63	762
Du Zhang United States	16	509 1.3×	162 0.8×	118 1.1×	79 0.8×	158 1.7×	73	934
Andreas Wichert Portugal	15	456 1.2×	106 0.5×	71 0.6×	25 0.2×	59 0.6×	77	745
Lu Zhou China	14	395 1.0×	127 0.6×	281 2.6×	315 3.1×	36 0.4×	60	769
Vlad P. Shmerko Canada	11	261 0.7×	69 0.3×	77 0.7×	29 0.3×	191 2.1×	71	577
Zheng Huang China	15	272 0.7×	248 1.2×	142 1.3×	153 1.5×	21 0.2×	62	764
Qin Li China	17	986 2.6×	195 0.9×	82 0.7×	53 0.5×	64 0.7×	84	1.3k
Paul Cuff United States	16	336 0.9×	144 0.7×	58 0.5×	386 3.8×	127 1.4×	48	1.0k
Nargis Bibi Pakistan	18	134 0.3×	476 2.2×	48 0.4×	70 0.7×	61 0.7×	40	719
Alan Mink United States	15	474 1.2×	355 1.7×	237 2.2×	74 0.7×	37 0.4×	50	1.0k

Countries citing papers authored by Takeshi Koshiba

Since Specialization

Citations

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

Fields of papers citing papers by Takeshi Koshiba

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Takeshi Koshiba

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

All Works

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20 of 20 papers shown

Ariaeenejad, Shohreh, Kaveh Kavousi, Behrouz Zolfaghari, et al.. (2023). Efficient bioconversion of lignocellulosic waste by a novel computationally screened hyperthermostable enzyme from a specialized microbiota. Ecotoxicology and Environmental Safety. 252. 114587–114587. 2 indexed citations

Dall’Arno, Michele, Francesco Buscemi, & Takeshi Koshiba. (2023). Computing the quantumguesswork: a quadratic assignment problem. Quantum Information and Computation. 23(9&10). 721–732. 1 indexed citations

Hayashi, Masahito & Takeshi Koshiba. (2023). Universal Adaptive Construction of Verifiable Secret Sharing and Its Application to Verifiable Secure Distributed Data Storage. IEEE/ACM Transactions on Networking. 32(1). 253–267. 2 indexed citations

Hayashi, Masahito & Takeshi Koshiba. (2022). Quantum verifiable protocol for secure modulo zero-sum randomness. Quantum Information Processing. 21(8). 7 indexed citations

Zolfaghari, Behrouz, et al.. (2022). From Random Numbers to Random Objects. Entropy. 24(7). 928–928. 2 indexed citations

Kowsher, Md., et al.. (2022). Bangla-BERT: Transformer-Based Efficient Model for Transfer Learning and Language Understanding. IEEE Access. 10. 91855–91870. 45 indexed citations

Arefin, Mohammad Shamsul, et al.. (2022). CARAN: A Context-Aware Recency-Based Attention Network for Point-of-Interest Recommendation. IEEE Access. 10. 36299–36310. 15 indexed citations

Zolfaghari, Behrouz & Takeshi Koshiba. (2022). The Dichotomy of Neural Networks and Cryptography: War and Peace. Applied System Innovation. 5(4). 61–61. 6 indexed citations

Kowsher, Md., et al.. (2022). An Enhanced Neural Word Embedding Model for Transfer Learning. Applied Sciences. 12(6). 2848–2848. 18 indexed citations

10.

Koshiba, Takeshi, et al.. (2022). Perfectly Secure Message Transmission Against Rational Adversaries. IEEE Journal on Selected Areas in Information Theory. 3(2). 390–404.

11.

Zolfaghari, Behrouz & Takeshi Koshiba. (2022). AI Makes Crypto Evolve. Applied System Innovation. 5(4). 75–75. 4 indexed citations

12.

Zolfaghari, Behrouz, et al.. (2022). The Odyssey of Entropy: Cryptography. Entropy. 24(2). 266–266. 17 indexed citations

13.

Deb, Kaushik, et al.. (2021). Traditional Bangladeshi Sports Video Classification Using Deep Learning Method. Applied Sciences. 11(5). 2149–2149. 22 indexed citations

14.

Deb, Kaushik, et al.. (2021). A Deep Learning Approach to Predict Autism Spectrum Disorder Using Multisite Resting-State fMRI. Applied Sciences. 11(8). 3636–3636. 84 indexed citations

15.

Koshiba, Takeshi, et al.. (2021). Efficient Private Conjunctive Query Protocol Over Encrypted Data. Cryptography. 5(1). 2–2. 1 indexed citations

16.

Hossain, Syed Md. Minhaz, Kaushik Deb, Pranab Kumar Dhar, & Takeshi Koshiba. (2021). Plant Leaf Disease Recognition Using Depth-Wise Separable Convolution-Based Models. Symmetry. 13(3). 511–511. 30 indexed citations

17.

Dhar, Pranab Kumar, et al.. (2020). Blind Audio Watermarking Based on Parametric Slant-Hadamard Transform and Hessenberg Decomposition. Symmetry. 12(3). 333–333. 5 indexed citations

18.

Yasuda, Masaya, et al.. (2016). Privacy-preserving fuzzy commitment for biometrics via layered error-correcting codes. Lecture notes in computer science. 9482. 117–133.

19.

Morimae, Tomoyuki & Takeshi Koshiba. (2014). Impossibility of perfectly-secure delegated quantum computing for classical client. arXiv (Cornell University). 5 indexed citations

20.

Koshiba, Takeshi, et al.. (2006). Round-Efficient One-Way Permutation Based Perfectly Concealing Bit Commitment Scheme. Electronic colloquium on computational complexity. 13. 3 indexed citations

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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