Lingzhi Sui

950 total citations · 1 hit paper
11 papers, 712 citations indexed

About

Lingzhi Sui is a scholar working on Computer Vision and Pattern Recognition, Electrical and Electronic Engineering and Artificial Intelligence. According to data from OpenAlex, Lingzhi Sui has authored 11 papers receiving a total of 712 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Computer Vision and Pattern Recognition, 6 papers in Electrical and Electronic Engineering and 4 papers in Artificial Intelligence. Recurrent topics in Lingzhi Sui's work include Advanced Neural Network Applications (9 papers), CCD and CMOS Imaging Sensors (4 papers) and Video Surveillance and Tracking Methods (3 papers). Lingzhi Sui is often cited by papers focused on Advanced Neural Network Applications (9 papers), CCD and CMOS Imaging Sensors (4 papers) and Video Surveillance and Tracking Methods (3 papers). Lingzhi Sui collaborates with scholars based in China and United States. Lingzhi Sui's co-authors include Jiantao Qiu, Song Yao, Huazhong Yang, Kaiyuan Guo, Song Han, Junbin Wang, Jincheng Yu, Yu Wang, Yi Shan and Lu Tian and has published in prestigious journals such as IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems.

In The Last Decade

Lingzhi Sui

11 papers receiving 696 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.

Angel-Eye: A Complete Design Flow for Mapping CNN Onto Embedded FPGA

2017 416 citations Kaiyuan Guo, Lingzhi Sui et al. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems profile →

Peers

Countries citing papers authored by Lingzhi Sui

Since Specialization

Citations

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

Fields of papers citing papers by Lingzhi Sui

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Lingzhi Sui

This figure shows the co-authorship network connecting the top 25 collaborators of Lingzhi Sui. A scholar is included among the top collaborators of Lingzhi Sui 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 Lingzhi Sui. Lingzhi Sui 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:

11 of 11 papers shown

#	Work	Indexed citations
1	LPAC: A Low-Precision Accelerator for CNN on FPGAs 2020 ·Tianyu Zhang, (unknown), Lu Tian, Yi Li, (unknown), (unknown), (unknown), (unknown), Lingzhi Sui, (unknown), (unknown), Michaela Blott, Yi Shan	2
2	A High-Performance CNN Processor Based on FPGA for MobileNets 2019 ·Di Wu, Yu Zhang, (unknown), Lu Tian, (unknown), Lingzhi Sui, (unknown), Yi Shan	98
3	An In-depth Comparison of Compilers for Deep Neural Networks on Hardware 2019 ·(unknown), Jian Weng, Yushun Wang, Lingzhi Sui, Yi Shan, Yu Wang	5
4	DNNVM 2019 ·(unknown), Shuang Liang, Lingzhi Sui, Zhen Zhang, Jiantao Qiu, (unknown), Xin Liu, Yushun Wang, Yi Shan, Yu Wang	10
5	DNNVM: End-to-End Compiler Leveraging Heterogeneous Optimizations on FPGA-Based CNN Accelerators 2019 ·IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems ·(unknown), Shuang Liang, Lingzhi Sui, (unknown), Jiantao Qiu, Xin Liu, Yushun Wang, Yi Shan, Yu Wang	60
6	Real-Time Object Detection and Semantic Segmentation Hardware System with Deep Learning Networks 2018 ·(unknown), Lu Tian, Junbin Wang, Shuang Liang, (unknown), Zhongmin Chen, Lingzhi Sui, Qian Yu, Xiaoming Sun, Yi Shan, Yu Wang	19
7	Angel-Eye: A Complete Design Flow for Mapping CNN Onto Embedded FPGA breakdown → 2017 ·IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems ·Kaiyuan Guo, Lingzhi Sui, Jiantao Qiu, Jincheng Yu, Junbin Wang, Song Yao, Song Han, Yu Wang, Huazhong Yang	416
8	From model to FPGA: Software-hardware co-design for efficient neural network acceleration 2016 ·Kaiyuan Guo, Lingzhi Sui, Jiantao Qiu, Song Yao, Song Han, (unknown), Huazhong Yang	41
9	Angel-Eye: A Complete Design Flow for Mapping CNN onto Customized Hardware 2016 ·Kaiyuan Guo, Lingzhi Sui, Jiantao Qiu, Song Yao, Song Han, Yu Wang, Huazhong Yang	53
10	Real-Time Pedestrian Detection and Tracking on Customized Hardware 2016 ·Junbin Wang, (unknown), Kaiyuan Guo, Jincheng Yu, Lingzhi Sui, Song Yao, Song Han, (unknown)	5
11	Time-varying channel estimation based on dynamic compressive sensing for OFDM systems 2014 ·Yanjun Han, Peiyao Zhao, Lingzhi Sui, (unknown)	3

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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