Yingcheng Lin

452 total citations
43 papers, 321 citations indexed

About

Yingcheng Lin is a scholar working on Electrical and Electronic Engineering, Computer Vision and Pattern Recognition and Artificial Intelligence. According to data from OpenAlex, Yingcheng Lin has authored 43 papers receiving a total of 321 indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Electrical and Electronic Engineering, 16 papers in Computer Vision and Pattern Recognition and 10 papers in Artificial Intelligence. Recurrent topics in Yingcheng Lin's work include Advanced Memory and Neural Computing (12 papers), CCD and CMOS Imaging Sensors (6 papers) and Advanced Neural Network Applications (6 papers). Yingcheng Lin is often cited by papers focused on Advanced Memory and Neural Computing (12 papers), CCD and CMOS Imaging Sensors (6 papers) and Advanced Neural Network Applications (6 papers). Yingcheng Lin collaborates with scholars based in China, United States and Canada. Yingcheng Lin's co-authors include Ye Wu, Jian Xu, Xichuan Zhou, Cong Shi, Nanjian Wu, Wei He, Liyuan Liu, Jiquan Yang, Hao Fu and Yan Hu and has published in prestigious journals such as SHILAP Revista de lepidopterología, Molecules and Sensors.

In The Last Decade

Yingcheng Lin

38 papers receiving 315 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Yingcheng Lin China 10 127 84 58 52 37 43 321
Hongyu Fu China 8 101 0.8× 68 0.8× 36 0.6× 45 0.9× 33 0.9× 36 297
A. Sreedevi India 14 200 1.6× 294 3.5× 47 0.8× 41 0.8× 136 3.7× 47 559
Wei Shao China 10 108 0.9× 259 3.1× 11 0.2× 44 0.8× 22 0.6× 43 433
Souvik Chakraborty United States 7 90 0.7× 171 2.0× 33 0.6× 55 1.1× 22 0.6× 23 313
Hang Su China 9 309 2.4× 179 2.1× 54 0.9× 132 2.5× 15 0.4× 19 532
Congjun Cao China 12 46 0.4× 58 0.7× 88 1.5× 118 2.3× 5 0.1× 36 347
Shengjie Liu China 10 422 3.3× 91 1.1× 38 0.7× 29 0.6× 53 1.4× 34 664
Byungjoo Lee South Korea 10 135 1.1× 140 1.7× 28 0.5× 35 0.7× 118 3.2× 24 376
Jingyi Qu China 12 156 1.2× 205 2.4× 31 0.5× 168 3.2× 86 2.3× 35 504

Countries citing papers authored by Yingcheng Lin

Since Specialization
Citations

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

Fields of papers citing papers by Yingcheng Lin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yingcheng Lin

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

All Works

20 of 20 papers shown
1.
Lin, Yingcheng, et al.. (2026). ATW-SNN: low-accuracy-loss asymmetric ternary-weight spiking neural network with spike calibration strategy. Neuromorphic Computing and Engineering. 6(1). 14006–14006.
2.
Chen, Guan‐Yu, et al.. (2025). An Edge Neuromorphic Processor With High-Accuracy On-Chip Aggregate-Label Learning. IEEE Transactions on Circuits & Systems II Express Briefs. 72(3). 509–513. 1 indexed citations
3.
Zhou, Xichuan, et al.. (2025). STOP: spatiotemporal orthogonal propagation for weight-threshold-leakage synergistic training of deep spiking neural networks. Neuromorphic Computing and Engineering. 5(4). 44001–44001.
4.
Lin, Yingcheng, et al.. (2024). MorphBungee-Lite: An Edge Neuromorphic Architecture With Balanced Cross-Core Workloads Based on Layer-Wise Event-Batch Learning/Inference. IEEE Transactions on Circuits & Systems II Express Briefs. 72(1). 293–297. 4 indexed citations
5.
Zhang, Ling, et al.. (2024). A High-Performance RDMA NIC With Ultrahighly Scalable Connections. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems. 44(6). 2156–2167.
6.
Shi, Cong, Haibing Wang, Yingcheng Lin, et al.. (2024). Ghost Reservoir: A Memory-Efficient Low-Power and Real-Time Neuromorphic Processor of Liquid State Machine With On-Chip Learning. IEEE Transactions on Circuits & Systems II Express Briefs. 71(10). 4526–4530. 4 indexed citations
7.
Zhang, Ling, S. Ye, Zhongru Gou, et al.. (2024). An Efficient Parallel CRC Computing Method for High Bandwidth Networks and FPGA Implementation. Electronics. 13(22). 4399–4399.
8.
Tian, Min, Haibing Wang, Junxian He, et al.. (2024). MorphBungee: A 65-nm 7.2-mm 2 27-µJ/Image Digital Edge Neuromorphic Chip With on-Chip 802-Frame/s Multi-Layer Spiking Neural Network Learning. IEEE Transactions on Biomedical Circuits and Systems. 19(1). 209–225. 4 indexed citations
9.
Zhou, Xichuan, et al.. (2023). Multi-Scale FPGA-Based Infrared Image Enhancement by Using RGF and CLAHE. Sensors. 23(19). 8101–8101. 10 indexed citations
10.
Yang, Ruoxi, Long Chen, Ling Zhang, et al.. (2023). Image Enhancement via Special Functions and Its Application for Near Infrared Imaging. SHILAP Revista de lepidopterología. 7(7). 2200179–2200179. 5 indexed citations
11.
Lin, Yingcheng, et al.. (2022). A Lightweight Attention-Based Network towards Distracted Driving Behavior Recognition. Applied Sciences. 12(9). 4191–4191. 12 indexed citations
12.
Lin, Yingcheng, Rui Li, Wei He, et al.. (2021). A Pixel-Parallel Array Processor without Computational Logic for Computational Image Sensors. 51–52. 2 indexed citations
13.
He, Wei, Jie Zhang, Yingcheng Lin, et al.. (2020). A Low-Cost High-Speed Object Tracking VLSI System Based on Unified Textural and Dynamic Compressive Features. IEEE Transactions on Circuits & Systems II Express Briefs. 68(3). 1013–1017. 4 indexed citations
14.
Lin, Yingcheng, et al.. (2020). An Energy-Efficient Bagged Binary Neural Network Accelerator. 174–179. 2 indexed citations
15.
Wu, Ye, Pengfei Ou, Frank R. Fronczek, et al.. (2019). Simultaneous Enhancement of Near-Infrared Emission and Dye Photodegradation in a Racemic Aspartic Acid Compound via Metal-Ion Modification. ACS Omega. 4(21). 19136–19144. 1 indexed citations
16.
Wu, Ye, Yingcheng Lin, & Jian Xu. (2019). Synthesis of Ag–Ho, Ag–Sm, Ag–Zn, Ag–Cu, Ag–Cs, Ag–Zr, Ag–Er, Ag–Y and Ag–Co metal organic nanoparticles for UV-Vis-NIR wide-range bio-tissue imaging. Photochemical & Photobiological Sciences. 18(5). 1081–1091. 95 indexed citations
17.
Wu, Ye, Hao Fu, Laibao Zhang, et al.. (2018). Toward a Rapid-Fabricated Triboelectric Device with a 1,3-Phosphorylated Poly(vinyl alcohol) Polymer for Water Turbulence Energy Harvesting. ACS Omega. 3(7). 8421–8428. 12 indexed citations
18.
Wu, Ye, Hao Fu, Bin Li, & Yingcheng Lin. (2017). Negative-resistance and high-mobility devices based on paper. Materials Express. 7(1). 5–14. 3 indexed citations
19.
Zhang, Ling, Qing Xu, Wei He, & Yingcheng Lin. (2017). Single view head pose estimation system based on SoC FPGA. 2. 369–374. 2 indexed citations
20.
Li, Wen, et al.. (2014). Surface modification of titanium substrates with silver nanoparticles embedded sulfhydrylated chitosan/gelatin polyelectrolyte multilayer films for antibacterial application. Journal of Materials Science Materials in Medicine. 25(6). 1435–1448. 18 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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