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Zibo Feng
ResearcherPublications, citations & collaboration network
Zibo Feng is a researcher indexed in ScholarIQ from OpenAlex & ORCID. ScholarIQ records 21 works, 18 citations, an h-index of 2 and an i10-index of 0.
21
Works
18
Citations
2
h-index
0
i10-index
IDs:OpenAlex
How has Zibo Feng's publication output changed over time?
ScholarIQpublication output · 2020–2026
Output grew400% over the shown period — from 1 works in 2020 to 5 in 2026.
1
3
1
1
5
20202021202420252026
What are the most-cited papers on Zibo Feng?
ScholarIQmost cited works
Reformer: Re-parameterized kernel lightweight transformer for grape disease segmentation
Xinxin Zhang, Zibo Feng, Weisong Mu
Expert Systems with Applications. 20247 Citations
Research on application of corner detection in thread vision measurement
Zibo Feng, Fucheng You, Junwei He
S4210187594. 20214 CitationsOPEN ACCESS
Neonicotinoids disrupt flight, bioenergetic homeostasis and neurotransmission in honey bees
Zepu Gao, Lin Ji, Wennan Luo, Zibo Feng, Xuebing Leng, Yongqiang Ma, Yaoguang Wei, Sen Pang, Diya An, Huizhe Lu
Journal of Hazardous Materials. 20262 Citations
Research on Video Processing Based on YOLOv3 Improved Algorithm
Zibo Feng, Fucheng You
S4306523680. 20201 Citations
Predicting Antegrade Success in Femoropopliteal Occlusions Using Radiological and Clinical Machine Learning Models
Xiaoxiang Zhou, Rong Fan, Xiaohu Meng, Xin Fang, Zibo Feng, Meng Ye, Hongkun Zhang, Chenyang Qiu, Ziheng Wu
CardioVascular and Interventional Radiology. 20251 Citations
Related on ScholarIQ
Beijing University of Posts and Telecommunications
Institution
Reformer: Re-parameterized kernel lightweight transformer for grape disease segmentation
Paper
Research on application of corner detection in thread vision measurement
Paper
Neonicotinoids disrupt flight, bioenergetic homeostasis and neurotransmission in honey bees
Paper
Research on Video Processing Based on YOLOv3 Improved Algorithm
Paper
Predicting Antegrade Success in Femoropopliteal Occlusions Using Radiological and Clinical Machine Learning Models
Paper