Zhong Qu

1.8k total citations
80 papers, 1.3k citations indexed

About

Zhong Qu is a scholar working on Computer Vision and Pattern Recognition, Civil and Structural Engineering and Aerospace Engineering. According to data from OpenAlex, Zhong Qu has authored 80 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 50 papers in Computer Vision and Pattern Recognition, 28 papers in Civil and Structural Engineering and 8 papers in Aerospace Engineering. Recurrent topics in Zhong Qu's work include Infrastructure Maintenance and Monitoring (28 papers), Advanced Neural Network Applications (22 papers) and Advanced Image and Video Retrieval Techniques (19 papers). Zhong Qu is often cited by papers focused on Infrastructure Maintenance and Monitoring (28 papers), Advanced Neural Network Applications (22 papers) and Advanced Image and Video Retrieval Techniques (19 papers). Zhong Qu collaborates with scholars based in China, United States and Germany. Zhong Qu's co-authors include Ling Liu, Shengye Wang, Qiang Zhou, Shiyan Wang, Cui‐Jin Li, Jing Mei, Ling Liu, Wen Chen, Li Zhang and Ling Liu and has published in prestigious journals such as PLoS ONE, IEEE Transactions on Image Processing and Expert Systems with Applications.

In The Last Decade

Zhong Qu

70 papers receiving 1.3k citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Zhong Qu China	21	670	434	207	194	115	80	1.3k
Vedhus Hoskere United States	16	1.3k 2.0×	328 0.8×	217 1.0×	117 0.6×	54 0.5×	33	1.6k
Yasutaka Narazaki United States	17	1.3k 1.9×	246 0.6×	233 1.1×	120 0.6×	44 0.4×	42	1.6k
Sijia Yu United States	6	714 1.1×	1.1k 2.5×	198 1.0×	110 0.6×	60 0.5×	13	1.9k
Yahui Liu China	14	737 1.1×	307 0.7×	232 1.1×	99 0.5×	120 1.0×	32	1.3k
Xiaohu Lu China	15	727 1.1×	457 1.1×	235 1.1×	107 0.6×	119 1.0×	38	1.4k
Ezzatollah Salari United States	16	441 0.7×	700 1.6×	78 0.4×	69 0.4×	140 1.2×	76	1.2k
Weiguo Gong China	20	344 0.5×	701 1.6×	143 0.7×	68 0.4×	356 3.1×	96	1.3k
Yichang Tsai United States	23	1.6k 2.4×	362 0.8×	272 1.3×	150 0.8×	140 1.2×	139	2.1k
Takehiro Kashiyama Japan	12	1.1k 1.6×	290 0.7×	187 0.9×	125 0.6×	92 0.8×	36	1.4k
Chuan‐Zhi Dong United States	20	1.4k 2.1×	590 1.4×	217 1.0×	100 0.5×	65 0.6×	35	1.7k

Countries citing papers authored by Zhong Qu

Since Specialization

Citations

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

Fields of papers citing papers by Zhong Qu

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Zhong Qu

This figure shows the co-authorship network connecting the top 25 collaborators of Zhong Qu. A scholar is included among the top collaborators of Zhong Qu 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 Zhong Qu. Zhong Qu 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

Li, Jie, et al.. (2025). A method of road damage detection for complex background images based on region guidance network. Pattern Recognition. 168. 111780–111780. 1 indexed citations

Qu, Zhong, et al.. (2025). A method for noise-suppressed multimodal feature integration in urban scene detection. Information Processing & Management. 62(6). 104290–104290.

Qu, Zhong, et al.. (2025). A method of object detection network with progressive feature fusion and reverse attention for traffic scenes. Signal Image and Video Processing. 19(11).

Qu, Zhong, et al.. (2024). A method of object detection with attention mechanism and C2f_DCNv2 for complex traffic scenes. Expert Systems with Applications. 267. 126141–126141. 3 indexed citations

Qu, Zhong, et al.. (2024). A Lightweight Network with Dual Encoder and Cross Feature Fusion for Cement Pavement Crack Detection. Computer Modeling in Engineering & Sciences. 140(1). 255–273. 1 indexed citations

Qu, Zhong, et al.. (2024). YOLOX-RDD: A Method of Anchor-Free Road Damage Detection for Front-View Images. IEEE Transactions on Intelligent Transportation Systems. 25(10). 14725–14739. 13 indexed citations

Qu, Zhong, et al.. (2024). A Directional Connectivity Feature Enhancement Network for Pavement Crack Detection. IEEE Transactions on Intelligent Transportation Systems. 26(1). 1039–1054. 5 indexed citations

Qu, Zhong, et al.. (2024). A method of hybrid dilated and global convolution networks for pavement crack detection. Multimedia Systems. 30(4). 1 indexed citations

Qu, Zhong, et al.. (2024). A Feature Fusion Network With Multiscale Adaptively Attentional for Object Detection in Complex Traffic Scenes. IEEE Transactions on Intelligent Vehicles. 10(8). 4217–4230.

10.

Li, Cui‐Jin, Zhong Qu, & Shengye Wang. (2023). A method of knowledge distillation based on feature fusion and attention mechanism for complex traffic scenes. Engineering Applications of Artificial Intelligence. 124. 106533–106533. 9 indexed citations

11.

Li, Cui‐Jin, Zhong Qu, & Shengye Wang. (2023). An object detection approach with residual feature fusion and second‐order term attention mechanism. CAAI Transactions on Intelligence Technology. 9(2). 411–424. 3 indexed citations

12.

Li, Cui‐Jin, et al.. (2023). PerspectiveNet: An Object Detection Method With Adaptive Perspective Box Network Based on Density-Aware. IEEE Transactions on Intelligent Transportation Systems. 24(5). 5419–5429. 8 indexed citations

13.

Qu, Zhong, et al.. (2022). A method of image stitching with partition matching and direct detection for rotated image. Displays. 75. 102316–102316. 3 indexed citations

14.

Li, Cui‐Jin, et al.. (2021). A method of cross-layer fusion multi-object detection and recognition based on improved faster R-CNN model in complex traffic environment. Pattern Recognition Letters. 145. 127–134. 45 indexed citations

15.

Qu, Zhong, Shuai Liu, & Yan Liu. (2019). Self-adaptive ViBe algorithm with time domain information. 40(3). 782–787. 2 indexed citations

16.

Qu, Zhong, et al.. (2019). Eliminating Lining Seams in Tunnel Concrete Crack Images via Line Segments’ Translation and Expansion. IEEE Access. 7. 30615–30627. 1 indexed citations

17.

Qu, Zhong, et al.. (2018). Concrete surface crack detection with the improved pre-extraction and the second percolation processing methods. PLoS ONE. 13(7). e0201109–e0201109. 20 indexed citations

18.

Qu, Zhong & Xin Huang. (2017). The foreground detection algorithm combined the temporal–spatial information and adaptive visual background extraction. The Imaging Science Journal. 65(1). 49–61. 7 indexed citations

19.

Qu, Zhong. (2008). Research on Emergency Information Decision Support System of Unexpected Events in Chongqing. Journal of Chongqing University of Posts and Telecommunications. 1 indexed citations

20.

Qu, Zhong & Yu Qiu. (2006). Research on Hash Algorithm of Packet Classify Into Flow.

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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