Deeksha Arya

1.1k total citations · 2 hit papers
18 papers, 605 citations indexed

About

Deeksha Arya is a scholar working on Civil and Structural Engineering, Ocean Engineering and Computer Vision and Pattern Recognition. According to data from OpenAlex, Deeksha Arya has authored 18 papers receiving a total of 605 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Civil and Structural Engineering, 9 papers in Ocean Engineering and 6 papers in Computer Vision and Pattern Recognition. Recurrent topics in Deeksha Arya's work include Infrastructure Maintenance and Monitoring (11 papers), Geophysical Methods and Applications (8 papers) and Asphalt Pavement Performance Evaluation (5 papers). Deeksha Arya is often cited by papers focused on Infrastructure Maintenance and Monitoring (11 papers), Geophysical Methods and Applications (8 papers) and Asphalt Pavement Performance Evaluation (5 papers). Deeksha Arya collaborates with scholars based in Japan, India and United States. Deeksha Arya's co-authors include Yoshihide Sekimoto, Hiroya Maeda, Durga Toshniwal, Sanjay Kumar Ghosh, Takehiro Kashiyama, Alexander Mráz, Hiroshi Omata, Mayank Dave, K. T. Arasu and Teena Sharma and has published in prestigious journals such as SHILAP Revista de lepidopterología, IEEE Transactions on Information Theory and IEEE Access.

In The Last Decade

Deeksha Arya

16 papers receiving 581 citations

Hit Papers

Deep learning-based road damage detection and classificat... 2021 2026 2022 2024 2021 2021 50 100 150
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Deep learning-based road damage detection and classification for multiple countries
    2021 181 citations Deeksha Arya, Hiroya Maeda et al. Automation in Construction profile →
  2. RDD2020: An annotated image dataset for automatic road damage detection using deep learning
    2021 155 citations Deeksha Arya, Hiroya Maeda et al. SHILAP Revista de lepidopterología profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Deeksha Arya Japan 9 532 188 161 72 67 18 605
Seung-Ki Ryu South Korea 12 534 1.0× 95 0.5× 114 0.7× 56 0.8× 96 1.4× 35 622
Hristina Georgieva Bulgaria 5 693 1.3× 69 0.4× 115 0.7× 21 0.3× 151 2.3× 10 807
Varun Kasireddy United States 7 724 1.4× 75 0.4× 113 0.7× 21 0.3× 145 2.2× 11 839
Sumathi Poobal India 6 552 1.0× 82 0.4× 66 0.4× 22 0.3× 151 2.3× 11 735
Arun K Mohan India 4 552 1.0× 79 0.4× 66 0.4× 19 0.3× 150 2.2× 8 679
Wenbo Hu China 12 218 0.4× 107 0.6× 64 0.4× 17 0.2× 83 1.2× 35 460
Zihao Xu China 8 238 0.4× 48 0.3× 67 0.4× 31 0.4× 64 1.0× 18 394
Van-Duc Tran Vietnam 9 436 0.8× 34 0.2× 68 0.4× 39 0.5× 117 1.7× 16 533
Xiaojun Wei China 12 405 0.8× 77 0.4× 32 0.2× 24 0.3× 154 2.3× 44 585
Fuwen Deng China 7 244 0.5× 52 0.3× 61 0.4× 31 0.4× 54 0.8× 13 518

Countries citing papers authored by Deeksha Arya

Since Specialization
Citations

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

Fields of papers citing papers by Deeksha Arya

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Deeksha Arya

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

All Works

18 of 18 papers shown
1.
Arya, Deeksha, Hiroya Maeda, & Yoshihide Sekimoto. (2024). From global challenges to local solutions: A review of cross-country collaborations and winning strategies in road damage detection. Advanced Engineering Informatics. 60. 102388–102388. 22 indexed citations
2.
3.
Arya, Deeksha, Hiroshi Omata, Hiroya Maeda, & Yoshihide Sekimoto. (2024). ORDDC’2024: State of the art Solutions for Optimized Road Damage Detection. 8430–8438. 5 indexed citations
4.
Sharma, Teena, et al.. (2024). Deep Learning-Based Object Detection and Classification for Autonomous Vehicles in Different Weather Scenarios of Quebec, Canada. IEEE Access. 12. 13648–13662. 13 indexed citations
5.
Arya, Deeksha, Hiroya Maeda, Sanjay Kumar Ghosh, Durga Toshniwal, & Yoshihide Sekimoto. (2024). RDD2022: A multi‐national image dataset for automatic road damage detection. Geoscience Data Journal. 31 indexed citations
6.
Arya, Deeksha, et al.. (2024). Federated learning–based global road damage detection. Computer-Aided Civil and Infrastructure Engineering. 39(14). 2223–2238. 9 indexed citations
7.
8.
Arya, Deeksha, et al.. (2022). Road Rutting Detection using Deep Learning on Images. 2022 IEEE International Conference on Big Data (Big Data). 1362–1368. 6 indexed citations
9.
Arya, Deeksha, Sanjay Kumar Ghosh, & Durga Toshniwal. (2022). AI-Driven Road Condition Monitoring across Multiple Nations. Proceedings of the AAAI Conference on Artificial Intelligence. 36(11). 12868–12869. 3 indexed citations
10.
Arya, Deeksha, Hiroya Maeda, Sanjay Kumar Ghosh, et al.. (2022). Crowdsensing-based Road Damage Detection Challenge (CRDDC’2022). 2022 IEEE International Conference on Big Data (Big Data). 6378–6386. 44 indexed citations
11.
Arya, Deeksha, Hiroya Maeda, Sanjay Kumar Ghosh, Durga Toshniwal, & Yoshihide Sekimoto. (2021). RDD2020: An annotated image dataset for automatic road damage detection using deep learning. SHILAP Revista de lepidopterología. 36. 107133–107133. 155 indexed citations breakdown →
12.
Arya, Deeksha, Hiroya Maeda, Sanjay Kumar Ghosh, et al.. (2021). Deep learning-based road damage detection and classification for multiple countries. Automation in Construction. 132. 103935–103935. 181 indexed citations breakdown →
13.
Arya, Deeksha. (2021). RDD2020: An Image Dataset for Smartphone-based Road Damage Detection and Classification. Data Archiving and Networked Services (DANS). 1. 12 indexed citations
14.
Arya, Deeksha, Hiroya Maeda, Sanjay Kumar Ghosh, et al.. (2020). Global Road Damage Detection: State-of-the-art Solutions. arXiv (Cornell University). 5533–5539. 108 indexed citations
15.
Arya, Deeksha & Mayank Dave. (2017). Security-based service broker policy for FOG computing environment. 1–6. 7 indexed citations
16.
Arasu, K. T., Deeksha Arya, & Deepak Kedia. (2016). Comparative analysis of punctured sequence pairs for frame synchronization applications. 33. 470–475. 1 indexed citations
17.
Arasu, K. T., et al.. (2015). Constructions of Punctured Difference Set Pairs and Their Corresponding Punctured Binary Array Pairs. IEEE Transactions on Information Theory. 61(4). 2191–2199. 5 indexed citations
18.
Arya, Deeksha, et al.. (2000). Video signal transmission for IS-95 environment. Electronics Letters. 36(5). 465–466.

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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