Linwei Ye

1.5k total citations · 1 hit paper
27 papers, 836 citations indexed

About

Linwei Ye is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Sensory Systems. According to data from OpenAlex, Linwei Ye has authored 27 papers receiving a total of 836 indexed citations (citations by other indexed papers that have themselves been cited), including 24 papers in Computer Vision and Pattern Recognition, 4 papers in Artificial Intelligence and 4 papers in Sensory Systems. Recurrent topics in Linwei Ye's work include Visual Attention and Saliency Detection (11 papers), Advanced Image and Video Retrieval Techniques (9 papers) and Advanced Neural Network Applications (8 papers). Linwei Ye is often cited by papers focused on Visual Attention and Saliency Detection (11 papers), Advanced Image and Video Retrieval Techniques (9 papers) and Advanced Neural Network Applications (8 papers). Linwei Ye collaborates with scholars based in China, Canada and United States. Linwei Ye's co-authors include Zhi Liu, Mrigank Rochan, Yang Wang, Liquan Shen, Guangling Sun, Yang Wang, Junhao Li, Xiaofei Zhou, Xiaoqin Zhang and Lina Li and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Sensors and Neurocomputing.

In The Last Decade

Linwei Ye

26 papers receiving 823 citations

Hit Papers

align trajectories

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.

Cross-Modal Self-Attention Network for Referring Image Segmentation

2019 329 citations Linwei Ye, Mrigank Rochan et al. profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Linwei Ye China	12	733	167	92	79	52	27	836
Yu Zeng China	11	510 0.7×	156 0.9×	46 0.5×	66 0.8×	77 1.5×	23	740
Huajun Zhou China	9	521 0.7×	48 0.3×	57 0.6×	90 1.1×	87 1.7×	19	614
Fatemeh Sadat Saleh Australia	7	548 0.7×	139 0.8×	48 0.5×	44 0.6×	84 1.6×	10	598
Jun Wei China	6	871 1.2×	120 0.7×	89 1.0×	162 2.1×	156 3.0×	13	1.0k
Jordi Pont-Tuset Switzerland	5	1.2k 1.7×	127 0.8×	22 0.2×	91 1.2×	31 0.6×	5	1.3k
Shafin Rahman Bangladesh	12	398 0.5×	267 1.6×	28 0.3×	33 0.4×	45 0.9×	58	584
Hae Jong Seo United States	10	469 0.6×	73 0.4×	34 0.4×	70 0.9×	30 0.6×	14	511
Lina Wei China	6	488 0.7×	47 0.3×	85 0.9×	59 0.7×	105 2.0×	17	544
Youwei Pang China	7	961 1.3×	57 0.3×	107 1.2×	174 2.2×	137 2.6×	15	1.1k
Jiangjian Xiao China	13	848 1.2×	53 0.3×	32 0.3×	83 1.1×	74 1.4×	60	928

Countries citing papers authored by Linwei Ye

Since Specialization

Citations

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

Fields of papers citing papers by Linwei Ye

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Linwei Ye

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

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

1.

Wu, Yong, et al.. (2024). TTAGaze: Self-Supervised Test-Time Adaptation for Personalized Gaze Estimation. IEEE Transactions on Circuits and Systems for Video Technology. 34(11). 10959–10971. 1 indexed citations

2.

Ye, Linwei, et al.. (2024). VELIE: A Vehicle-Based Efficient Low-Light Image Enhancement Method for Intelligent Vehicles. Sensors. 24(4). 1345–1345. 3 indexed citations

3.

Wang, Fei & Linwei Ye. (2023). The Impact of Novel Coronavirus Pneumonia Normalization on Cross Border E-commerce Development. 1 indexed citations

4.

Wang, Dong & Linwei Ye. (2023). UAV Image Denoising based on Swin Deformer for Power System Condition Monitoring. 388–391.

5.

Ye, Linwei, et al.. (2023). LLOD:A Object Detection Method Under Low-Light Condition by Feature Enhancement and Fusion. 659–662. 2 indexed citations

6.

Luo, Xinhui, Zhi Liu, Linwei Ye, et al.. (2022). Few-shot personalized saliency prediction using meta-learning. Image and Vision Computing. 124. 104491–104491. 11 indexed citations

7.

Ye, Linwei, et al.. (2022). Region-of-interest and channel attention-based joint optimization of image compression and computer vision. Neurocomputing. 500. 13–25. 16 indexed citations

8.

Bai, Zhen, Zhi Liu, Gongyang Li, Linwei Ye, & Yang Wang. (2021). Circular Complement Network for RGB-D Salient Object Detection. Neurocomputing. 451. 95–106. 12 indexed citations

9.

Wu, Yong, Zhi Liu, Xiaofei Zhou, Linwei Ye, & Yang Wang. (2021). ATCC: Accurate tracking by criss-cross location attention. Image and Vision Computing. 111. 104188–104188. 4 indexed citations

10.

Chen, Minyu, Zhi Liu, Linwei Ye, & Yang Wang. (2020). Attentional coarse-and-fine generative adversarial networks for image inpainting. Neurocomputing. 405. 259–269. 20 indexed citations

11.

Ye, Linwei, Mrigank Rochan, Zhi Liu, & Yang Wang. (2019). Cross-Modal Self-Attention Network for Referring Image Segmentation. 10494–10503. 329 indexed citations breakdown →

12.

Liu, Zhi, et al.. (2019). Weakly labeled fine-grained classification with hierarchy relationship of fine and coarse labels. Journal of Visual Communication and Image Representation. 63. 102584–102584. 4 indexed citations

13.

Liu, Zhi, et al.. (2019). Saliency detection via multi-level integration and multi-scale fusion neural networks. Neurocomputing. 364. 310–321. 24 indexed citations

14.

Ye, Linwei, et al.. (2018). Privacy-Preserving Age Estimation for Content Rating. 10. 1–6. 6 indexed citations

15.

Ye, Linwei, Zhi Liu, & Yang Wang. (2018). Learning Semantic Segmentation with Diverse Supervision. 1461–1469. 7 indexed citations

16.

Ye, Linwei, Zhi Liu, Lina Li, et al.. (2017). Salient Object Segmentation via Effective Integration of Saliency and Objectness. IEEE Transactions on Multimedia. 19(8). 1742–1756. 69 indexed citations

17.

Ye, Linwei, Zhi Liu, & Yang Wang. (2017). Depth-aware object instance segmentation. 11 indexed citations

18.

Ye, Linwei, Zhi Liu, Xiaofei Zhou, Liquan Shen, & Jian Zhang. (2016). Saliency Detection Via Similar Image Retrieval. IEEE Signal Processing Letters. 23(6). 838–842. 7 indexed citations

19.

Ye, Linwei, Zhi Liu, Junhao Li, Wan‐Lei Zhao, & Liquan Shen. (2015). Co-Saliency Detection via Co-Salient Object Discovery and Recovery. IEEE Signal Processing Letters. 22(11). 2073–2077. 47 indexed citations

20.

Ye, Linwei, Zhi Liu, & Lina Li. (2015). Evaluation on fusion of saliency and objectness for salient object segmentation. 1–4. 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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