Baosheng Yu

6.2k total citations · 3 hit papers
81 papers, 3.6k citations indexed

About

Baosheng Yu is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Nuclear and High Energy Physics. According to data from OpenAlex, Baosheng Yu has authored 81 papers receiving a total of 3.6k indexed citations (citations by other indexed papers that have themselves been cited), including 38 papers in Computer Vision and Pattern Recognition, 37 papers in Artificial Intelligence and 11 papers in Nuclear and High Energy Physics. Recurrent topics in Baosheng Yu's work include Domain Adaptation and Few-Shot Learning (19 papers), Multimodal Machine Learning Applications (14 papers) and Human Pose and Action Recognition (12 papers). Baosheng Yu is often cited by papers focused on Domain Adaptation and Few-Shot Learning (19 papers), Multimodal Machine Learning Applications (14 papers) and Human Pose and Action Recognition (12 papers). Baosheng Yu collaborates with scholars based in China, Australia and United States. Baosheng Yu's co-authors include Dacheng Tao, Jianping Gou, Stephen J. Maybank, Yibing Zhan, Zhi Hou, Bo Du, Lixiang Ru, Kun Li, R.D.K. Misra and Shaohua Wan and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Image Processing and Materials Science and Engineering A.

In The Last Decade

Baosheng Yu

79 papers receiving 3.5k 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.

Knowledge Distillation: A Survey

2021 1.9k citations Jianping Gou, Baosheng Yu et al. International Journal of Computer Vision profile →
Learning Affinity from Attention: End-to-End Weakly-Supervised Semantic Segmentation with Transformers

2022 160 citations Yibing Zhan, Baosheng Yu et al. 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) profile →
Contrastive Boundary Learning for Point Cloud Segmentation

2022 114 citations Yibing Zhan, Baosheng Yu et al. 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) profile →

Peers

Countries citing papers authored by Baosheng Yu

Since Specialization

Citations

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

Fields of papers citing papers by Baosheng Yu

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Baosheng Yu

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

20 of 20 papers shown

#	Work	Indexed citations
1	Hypnos: A domain-specific large language model for anesthesiology 2025 ·Neurocomputing ·(unknown), Jie Jiang, Yibing Zhan, (unknown), (unknown), Chong Zhang, Baosheng Yu, Liang Ding, (unknown), Jun Peng, Lin Xu, (unknown)	5
2	Intra-class progressive and adaptive self-distillation 2025 ·Neural Networks ·Jianping Gou, (unknown), (unknown), Weihua Ou, Baosheng Yu, Yi Zhang	1
3	Learning to Explore Sample Relationships 2025 ·IEEE Transactions on Pattern Analysis and Machine Intelligence ·Zhi Hou, Baosheng Yu, Chaoyue Wang, Yibing Zhan, Dacheng Tao	1
4	Semantics-Oriented Multitask Learning for DeepFake Detection: A Joint Embedding Approach 2025 ·IEEE Transactions on Circuits and Systems for Video Technology ·(unknown), Baosheng Yu, Yibing Zhan, Siwei Lyu, Kede Ma	1
5	Semantic Contextualization of Face Forgery: A New Definition, Dataset, and Detection Method 2025 ·IEEE Transactions on Information Forensics and Security ·(unknown), Baosheng Yu, Yibing Zhan, Siwei Lyu, Kede Ma	2
6	Self-Supervised Learning for Detecting AI-Generated Faces as Anomalies 2025 ·(unknown), Baosheng Yu, Yibing Zhan, Kede Ma	0
7	Fine-Tuning LLMs for Anesthesiology via Compositional Data Generation 2025 ·IEEE Transactions on Emerging Topics in Computational Intelligence ·Yanhong Li, Yibing Zhan, Baosheng Yu, (unknown), Chong Zhang, Da Zhu, (unknown), (unknown), Liang Ding, Weifeng Liu, (unknown), Dapeng Tao	0
8	Pseudo Contrastive Learning for graph-based semi-supervised learning 2025 ·Neurocomputing ·(unknown), Ziyu Guan, Wei Zhao, (unknown), (unknown), Lining Xing, Baosheng Yu, Dacheng Tao	5
9	Graph Convolutional Networks With Collaborative Feature Fusion for Sequential Recommendation 2024 ·IEEE Transactions on Big Data ·Jianping Gou, (unknown), Yibing Zhan, Baosheng Yu, Weihua Ou, Yi Zhang	2
10	Explicit and Implicit Box Equivariance Learning for Weakly-Supervised Rotated Object Detection 2024 ·IEEE Transactions on Emerging Topics in Computational Intelligence ·(unknown), Yibing Zhan, Xu Lin, Baosheng Yu, Liang Ding, Jianqing Zhu, Dapeng Tao	4
11	On exploring node-feature and graph-structure diversities for node drop graph pooling 2023 ·Neural Networks ·Chuang Liu, Yibing Zhan, Baosheng Yu, Liu Liu, Bo Du, Wenbin Hu, Tongliang Liu	11
12	Multi-target Knowledge Distillation via Student Self-reflection 2023 ·International Journal of Computer Vision ·Jianping Gou, (unknown), Baosheng Yu, Lan Du, Yibing Zhan, Dacheng Tao	33
13	Feature-preserved convolutional neural network for 3D mesh recognition 2022 ·Applied Soft Computing ·(unknown), (unknown), Xian‐Tao Zeng, Baosheng Yu	9
14	BatchFormer: Learning to Explore Sample Relationships for Robust Representation Learning 2022 ·2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) ·Zhi Hou, Baosheng Yu, Dacheng Tao	69
15	Heatmap Regression via Randomized Rounding 2021 ·IEEE Transactions on Pattern Analysis and Machine Intelligence ·Baosheng Yu, Dacheng Tao	21
16	Contrastive Graph Poisson Networks: Semi-Supervised Learning with Extremely Limited Labels 2021 ·Griffith Research Online (Griffith University, Queensland, Australia) ·Sheng Wan, Yibing Zhan, Liu Liu, Baosheng Yu, Shirui Pan, Chen Gong	19
17	Skeleton edge motion networks for human action recognition 2020 ·Neurocomputing ·Haoran Wang, Baosheng Yu, (unknown), (unknown), Xin Zuo	42
18	Deep Multi-View Feature Learning for Person Re-Identification 2017 ·IEEE Transactions on Circuits and Systems for Video Technology ·Dapeng Tao, Yanan Guo, Baosheng Yu, Jianxin Pang, Zhengtao Yu	88
19	CMOS NBTI degradation and recovery behaviors in a wide temperature range 2010 ·Xiaoli Ji, Yiming Liao, Baosheng Yu, Feng Yan, (unknown), (unknown), Qiang Guo	1
20	JENDL Fusion File 99. 2002 ·Journal of Nuclear Science and Technology ·Satoshi Chiba, Tokio Fukahori, Keiichi SHIBATA, Baosheng Yu, Kazuaki Kosako, N. Yamamuro	9

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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