Dilin Wang is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Signal Processing.
According to data from OpenAlex, Dilin Wang has authored 22 papers receiving a total of 603 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Artificial Intelligence, 11 papers in Computer Vision and Pattern Recognition and 4 papers in Signal Processing. Recurrent topics in Dilin Wang's work include Advanced Neural Network Applications (8 papers), Domain Adaptation and Few-Shot Learning (5 papers) and Speech and Audio Processing (3 papers). Dilin Wang is often cited by papers focused on Advanced Neural Network Applications (8 papers), Domain Adaptation and Few-Shot Learning (5 papers) and Speech and Audio Processing (3 papers). Dilin Wang collaborates with scholars based in United States, Israel and China. Dilin Wang's co-authors include Vikas Chandra, Chengyue Gong, Qiang Liu, David Z. Pan, Qiang Liu, Jiaqi Gu, Hyoukjun Kwon, Meng Li, Yu‐Hsin Chen and Liangzhen Lai and has published in prestigious journals such as 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), arXiv (Cornell University) and Neural Information Processing Systems.
In The Last Decade
Dilin Wang
18 papers
receiving
581 citations
Hit Papers
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.
Multi-Scale High-Resolution Vision Transformer for Semantic Segmentation
2022167 citationsJiaqi Gu, Hyoukjun Kwon et al.2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)profile →
EfficientSAM: Leveraged Masked Image Pretraining for Efficient Segment Anything
202474 citationsYunyang Xiong, Lemeng Wu et al.profile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
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This map shows the geographic impact of Dilin Wang'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 Dilin Wang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dilin Wang more than expected).
This network shows the impact of papers produced by Dilin Wang. 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 Dilin Wang. The network helps show where Dilin Wang may publish in the future.
Co-authorship network of co-authors of Dilin Wang
This figure shows the co-authorship network connecting the top 25 collaborators of Dilin Wang.
A scholar is included among the top collaborators of Dilin Wang 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 Dilin Wang. Dilin Wang is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Wang, Dilin & Qiang Liu. (2018). An Optimization View on Dynamic Routing Between Capsules. International Conference on Learning Representations.57 indexed citations
19.
Wang, Dilin, et al.. (2018). Stein Variational Gradient Descent as Moment Matching. Neural Information Processing Systems. 31. 8854–8863.5 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.