Ruixin Yang

401 total citations · 1 hit paper
12 papers, 220 citations indexed

About

Ruixin Yang is a scholar working on Artificial Intelligence, Computer Networks and Communications and Computer Vision and Pattern Recognition. According to data from OpenAlex, Ruixin Yang has authored 12 papers receiving a total of 220 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Artificial Intelligence, 5 papers in Computer Networks and Communications and 5 papers in Computer Vision and Pattern Recognition. Recurrent topics in Ruixin Yang's work include Advanced Database Systems and Queries (3 papers), Data Management and Algorithms (3 papers) and Advanced Computational Techniques and Applications (3 papers). Ruixin Yang is often cited by papers focused on Advanced Database Systems and Queries (3 papers), Data Management and Algorithms (3 papers) and Advanced Computational Techniques and Applications (3 papers). Ruixin Yang collaborates with scholars based in United States, China and Denmark. Ruixin Yang's co-authors include Yingyan Yu, M. Kafatos, Changzhou Wang, Daniel Ziskin, Miikka Silfverberg, B. Doty, James L. Kinter, Dan Zhou, Changbing Yang and Garrett Nicolai and has published in prestigious journals such as Sensors, Remote Sensing and Frontiers in Oncology.

In The Last Decade

Ruixin Yang

9 papers receiving 213 citations

Hit Papers

Artificial Convolutional Neural Network in Object Detecti... 2021 2026 2022 2024 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. Artificial Convolutional Neural Network in Object Detection and Semantic Segmentation for Medical Imaging Analysis
    2021 189 citations Ruixin Yang, Yingyan Yu Frontiers in Oncology profile →

Peers

Ruixin Yang
M. Ramya India
Neetu Mittal India
Sameh Abd El-Ghany Saudi Arabia
Riaz Ali China
Chaoyu Chen China
Guanghua Tan China
Daxin Zhu China
K. Suganthi India
Sandra Jardim Portugal
Ahmad MohdAziz Hussein Saudi Arabia
M. Ramya India
Ruixin Yang
Citations per year, relative to Ruixin Yang Ruixin Yang (= 1×) peers M. Ramya

Countries citing papers authored by Ruixin Yang

Since Specialization
Citations

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

Fields of papers citing papers by Ruixin Yang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ruixin Yang

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

All Works

12 of 12 papers shown
1.
Yang, Ruixin, et al.. (2025). YOLO-SAD for fire detection and localization in real-world images. Digital Signal Processing. 165. 105320–105320.
2.
Yang, Ruixin, et al.. (2025). A Progressive Saliency-Guided Small Ship Detection Method for Large-Scene SAR Images. Remote Sensing. 17(17). 3085–3085.
3.
Zhou, Dan, et al.. (2024). Mining the Micro-Trajectory of Two-Wheeled Non-Motorized Vehicles Based on the Improved YOLOx. Sensors. 24(3). 759–759. 3 indexed citations
4.
Chen, Haitian, et al.. (2023). Deep Learning-Based Bloom Filter for Efficient Multi-key Membership Testing. Data Science and Engineering. 8(3). 234–246. 1 indexed citations
5.
Yang, Changbing, Ruixin Yang, Garrett Nicolai, & Miikka Silfverberg. (2022). Generalizing Morphological Inflection Systems to Unseen Lemmas. 226–235. 2 indexed citations
6.
Yang, Ruixin & Yingyan Yu. (2021). Artificial Convolutional Neural Network in Object Detection and Semantic Segmentation for Medical Imaging Analysis. Frontiers in Oncology. 11. 638182–638182. 189 indexed citations breakdown →
7.
8.
Yang, Ruixin, et al.. (2003). A distributed enhanced server for multidimensional scientific data. Computing in Science & Engineering. 5(2). 44–52. 3 indexed citations
9.
Yang, Ruixin, et al.. (2003). Remote data access via the SIESIP distributed information system. 284–284.
10.
Kafatos, M., Hannah K. Weir, Paul Hertz, et al.. (2002). The Virtual Domain Application Data Center: serving interdisciplinary Earth scientists. 264–276. 4 indexed citations
11.
12.
Yang, Ruixin, et al.. (2002). An XML-based distributed metadata server (DIMES) supporting Earth science metadata. 251–256. 8 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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