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.
Deep Residual Learning for Image Recognition
2016132.1k citationsKaiming He, Xiangyu Zhang et al.LA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Científicas)profile →
Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks
201638.0k citationsShaoqing Ren, Kaiming He et al.IEEE Transactions on Pattern Analysis and Machine Intelligenceprofile →
Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification
201511.2k citationsKaiming He, Xiangyu Zhang et al.profile →
Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks
201510.8k citationsShaoqing Ren, Kaiming He et al.arXiv (Cornell University)profile →
Spatial Pyramid Pooling in Deep Convolutional Networks for Visual Recognition
20158.1k citationsKaiming He, Xiangyu Zhang et al.IEEE Transactions on Pattern Analysis and Machine Intelligenceprofile →
Face Alignment at 3000 FPS via Regressing Local Binary Features
2014550 citationsShaoqing Ren, Xudong Cao et al.profile →
Object Detection Networks on Convolutional Feature Maps
2016320 citationsShaoqing Ren, Kaiming He et al.IEEE Transactions on Pattern Analysis and Machine Intelligenceprofile →
This map shows the geographic impact of Shaoqing Ren'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 Shaoqing Ren with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Shaoqing Ren more than expected).
This network shows the impact of papers produced by Shaoqing Ren. 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 Shaoqing Ren. The network helps show where Shaoqing Ren may publish in the future.
Co-authorship network of co-authors of Shaoqing Ren
This figure shows the co-authorship network connecting the top 25 collaborators of Shaoqing Ren.
A scholar is included among the top collaborators of Shaoqing Ren 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 Shaoqing Ren. Shaoqing Ren is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
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.