Song Mao

736 total citations
30 papers, 528 citations indexed

About

Song Mao is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Electrical and Electronic Engineering. According to data from OpenAlex, Song Mao has authored 30 papers receiving a total of 528 indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Computer Vision and Pattern Recognition, 7 papers in Artificial Intelligence and 5 papers in Electrical and Electronic Engineering. Recurrent topics in Song Mao's work include Handwritten Text Recognition Techniques (14 papers), Image Retrieval and Classification Techniques (7 papers) and Image Processing and 3D Reconstruction (5 papers). Song Mao is often cited by papers focused on Handwritten Text Recognition Techniques (14 papers), Image Retrieval and Classification Techniques (7 papers) and Image Processing and 3D Reconstruction (5 papers). Song Mao collaborates with scholars based in United States, China and Germany. Song Mao's co-authors include Tapas Kanungo, Azriel Rosenfeld, Chenyi Zhao, Yabin Ye, Chenglin Zhao, Zheng Zhou, Jong Woo Kim, Yimin Shi, Grid Thoma and George R. Thoma and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Communications of the ACM and IEEE Transactions on Image Processing.

In The Last Decade

Song Mao

29 papers receiving 485 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Song Mao United States 10 254 168 132 97 38 30 528
Yuwen Pan China 10 130 0.5× 96 0.6× 107 0.8× 78 0.8× 12 0.3× 19 394
Amir Hossein Jahangir Iran 13 52 0.2× 337 2.0× 128 1.0× 112 1.2× 76 2.0× 54 455
Rein Vesilo Australia 15 82 0.3× 351 2.1× 306 2.3× 34 0.4× 22 0.6× 64 642
P. Chenna Reddy India 11 213 0.8× 195 1.2× 86 0.7× 86 0.9× 50 1.3× 76 514
Aggeliki Sgora Greece 14 88 0.3× 450 2.7× 372 2.8× 26 0.3× 17 0.4× 42 611
Yu-Xiang Wang China 5 35 0.1× 157 0.9× 90 0.7× 104 1.1× 38 1.0× 12 350
Gunjan Gupta United States 7 38 0.1× 529 3.1× 264 2.0× 81 0.8× 45 1.2× 12 650
P. Balasubramanie India 10 27 0.1× 123 0.7× 59 0.4× 102 1.1× 76 2.0× 61 282
Bernd E. Wolfinger Germany 10 51 0.2× 328 2.0× 171 1.3× 16 0.2× 43 1.1× 57 401
Ing-Yi Chen Taiwan 11 26 0.1× 238 1.4× 206 1.6× 60 0.6× 81 2.1× 41 423

Countries citing papers authored by Song Mao

Since Specialization
Citations

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

Fields of papers citing papers by Song Mao

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Song Mao

This figure shows the co-authorship network connecting the top 25 collaborators of Song Mao. A scholar is included among the top collaborators of Song Mao 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 Song Mao. Song Mao 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
1.
Wang, Liang, Shuo‐Jye Wu, Sanku Dey, Yogesh Mani Tripathi, & Song Mao. (2023). Estimation of stress-strength reliability for multicomponent system with a generalized inverted exponential distribution. Stochastic Models. 39(4). 715–740. 2 indexed citations
2.
Mao, Song, et al.. (2021). Statistical Inference for a Simple Step Stress Model with Competing Risks Based on Generalized Type-I Hybrid Censoring. 系统科学与信息学报(英文). 9(5). 533–548. 2 indexed citations
3.
Mao, Song, Yimin Shi, & Xiaolin Wang. (2017). Exact inference for joint Type-I hybrid censoring model with exponential competing risks data. Acta Mathematicae Applicatae Sinica English Series. 33(3). 645–658. 2 indexed citations
4.
Mao, Song, et al.. (2014). Design of Smart Home System Based on Zigbee. Applied Mechanics and Materials. 635-637. 1086–1089. 13 indexed citations
5.
Mao, Song, et al.. (2014). A Survey on Infrared Weak Small Target Detection Method. Advanced materials research. 945-949. 1558–1560. 2 indexed citations
6.
Mao, Song, et al.. (2013). Exact inference for competing risks model with generalized type-I hybrid censored exponential data. Journal of Statistical Computation and Simulation. 84(11). 2506–2521. 21 indexed citations
7.
Mao, Song, Chenglin Zhao, Zheng Zhou, & Yabin Ye. (2012). An Improved Fuzzy Unequal Clustering Algorithm for Wireless Sensor Network. Mobile Networks and Applications. 18(2). 206–214. 77 indexed citations
8.
Mao, Song & Chenyi Zhao. (2011). Unequal clustering algorithm for WSN based on fuzzy logic and improved ACO. The Journal of China Universities of Posts and Telecommunications. 18(6). 89–97. 70 indexed citations
9.
Mao, Song, et al.. (2011). An improved fuzzy unequal clustering algorithm for wireless sensor network. 245–250. 16 indexed citations
10.
11.
Mao, Song & Tapas Kanungo. (2006). PSET: A Page Segmentation Evaluation Toolkit. 2 indexed citations
12.
Kanungo, Tapas, et al.. (2005). The Bible and multilingual optical character recognition. Communications of the ACM. 48(6). 124–130. 8 indexed citations
13.
Mao, Song, Jong Woo Kim, & Grid Thoma. (2004). A dynamic feature generation system for automated metadata extraction in preservation of digital materials. 225–232. 21 indexed citations
14.
Mao, Song, Azriel Rosenfeld, & Tapas Kanungo. (2003). <title>Document structure analysis algorithms: a literature survey</title>. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 5010. 197–207. 123 indexed citations
15.
Kanungo, Tapas & Song Mao. (2003). Stochastic language models for style-directed layout analysis of document images. IEEE Transactions on Image Processing. 12(5). 583–596. 11 indexed citations
16.
Mao, Song & Tapas Kanungo. (2002). Software architecture of PSET: a page segmentation evaluation toolkit. International Journal on Document Analysis and Recognition (IJDAR). 4(3). 205–217. 25 indexed citations
17.
Mao, Song & Tapas Kanungo. (2001). Stochastic Language Models for Automatic Acquisition of Lexicons from Printed Bilingual Dictionaries. 3 indexed citations
18.
Mao, Song & Tapas Kanungo. (2001). Empirical performance evaluation methodology and its application to page segmentation algorithms. IEEE Transactions on Pattern Analysis and Machine Intelligence. 23(3). 242–256. 64 indexed citations
19.
Mao, Song & Tapas Kanungo. (1999). A Methodology for Empirical Performance Evaluation of Page Segmentation Algorithms. Defense Technical Information Center (DTIC). 7 indexed citations
20.
Mao, Song & Tapas Kanungo. (1999). <title>Empirical performance evaluation of page segmentation algorithms</title>. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 3967. 303–314. 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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