Wenze Hu

428 total citations
25 papers, 207 citations indexed

About

Wenze Hu is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Aerospace Engineering. According to data from OpenAlex, Wenze Hu has authored 25 papers receiving a total of 207 indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Computer Vision and Pattern Recognition, 6 papers in Artificial Intelligence and 5 papers in Aerospace Engineering. Recurrent topics in Wenze Hu's work include Advanced Image and Video Retrieval Techniques (9 papers), Advanced Neural Network Applications (8 papers) and Advanced Vision and Imaging (6 papers). Wenze Hu is often cited by papers focused on Advanced Image and Video Retrieval Techniques (9 papers), Advanced Neural Network Applications (8 papers) and Advanced Vision and Imaging (6 papers). Wenze Hu collaborates with scholars based in China, United States and United Kingdom. Wenze Hu's co-authors include Song‐Chun Zhu, Ying Wu, Haifeng Gong, Jianwen Xie, Tianfu Wu, Bo Li, Xia Zhang, Xiaoyu Wang, Haokui Zhang and Yi Hong and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Carbohydrate Polymers and Pattern Recognition.

In The Last Decade

Wenze Hu

24 papers receiving 195 citations

Peers

Wenze Hu
Xindi Zhang China
Abdul Rehman Pakistan
B. Karthik India
Kiana Ehsani United States
Jingjing Qian China
Daniel Cabrini Hauagge United States
Zhuoran Shen Hong Kong
Yingjie Liu China
Ruojin Cai United States
Radim Tyleček United Kingdom
Xindi Zhang China
Wenze Hu
Citations per year, relative to Wenze Hu Wenze Hu (= 1×) peers Xindi Zhang

Countries citing papers authored by Wenze Hu

Since Specialization
Citations

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

Fields of papers citing papers by Wenze Hu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Wenze Hu

This figure shows the co-authorship network connecting the top 25 collaborators of Wenze Hu. A scholar is included among the top collaborators of Wenze Hu 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 Wenze Hu. Wenze Hu 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.
Huang, Kun, et al.. (2024). Graph-based social relation inference with multi-level conditional attention. Neural Networks. 173. 106216–106216. 5 indexed citations
2.
Hu, Wenze, Yaowei Wang, Yonghong Tian, et al.. (2023). Universal Object Detection with Large Vision Model. International Journal of Computer Vision. 132(4). 1258–1276. 5 indexed citations
3.
Hu, Wenze, et al.. (2023). Review of deep learning-based weed identification in crop fields. International journal of agricultural and biological engineering. 16(4). 1–10. 5 indexed citations
4.
Xu, Rui‐Hua, Haokui Zhang, Wenze Hu, Shiliang Zhang, & Xiaoyu Wang. (2023). ParCNetV2: Oversized Kernel with Enhanced Attention*. 5729–5739. 3 indexed citations
5.
Zhang, Haokui, Wenze Hu, & Xiaoyu Wang. (2023). Fcaformer: Forward Cross Attention in Hybrid Vision Transformer. Rare & Special e-Zone (The Hong Kong University of Science and Technology). 6037–6046. 4 indexed citations
6.
Zhang, Haokui, et al.. (2023). NAR-Former: Neural Architecture Representation Learning Towards Holistic Attributes Prediction. 7715–7724. 5 indexed citations
7.
Li, Pu, Hui Zheng, Miao Li, et al.. (2022). Effect of pH value and the distance between the electrodes on physicochemical properties of chitosan under SPP treatment. Carbohydrate Polymers. 288. 119348–119348. 3 indexed citations
8.
Hu, Wenze, et al.. (2022). Effect of solution pulsed plasma process on the degradation and physicochemical properties of pectin. Food Hydrocolloids. 136. 108236–108236. 21 indexed citations
9.
Hu, Wenze, et al.. (2022). LUMDE: Light-Weight Unsupervised Monocular Depth Estimation via Knowledge Distillation. Applied Sciences. 12(24). 12593–12593. 3 indexed citations
10.
Xie, Jianwen, Wenze Hu, Song‐Chun Zhu, & Ying Wu. (2014). Learning Sparse FRAME Models for Natural Image Patterns. International Journal of Computer Vision. 114(2-3). 91–112. 27 indexed citations
11.
Dai, Jifeng, Yi Hong, Wenze Hu, Song‐Chun Zhu, & Ying Wu. (2014). Unsupervised Learning of Dictionaries of Hierarchical Compositional Models. 32. 2505–2512. 8 indexed citations
12.
Hu, Wenze & Song‐Chun Zhu. (2014). Learning 3D Object Templates by Quantizing Geometry and Appearance Spaces. IEEE Transactions on Pattern Analysis and Machine Intelligence. 37(6). 1190–1205. 7 indexed citations
13.
Li, Bo, et al.. (2014). Coupling-and-decoupling: A hierarchical model for occlusion-free object detection. Pattern Recognition. 47(10). 3254–3264. 4 indexed citations
14.
Xie, Jianwen, Wenze Hu, Song‐Chun Zhu, & Ying Wu. (2014). Learning Inhomogeneous FRAME Models for Object Patterns. 2. 1035–1042. 3 indexed citations
15.
Hong, Yi, Zhangzhang Si, Wenze Hu, Song‐Chun Zhu, & Ying Wu. (2013). Unsupervised learning of compositional sparse code for natural image representation. Quarterly of Applied Mathematics. 72(2). 373–406. 8 indexed citations
16.
Hu, Wenze, et al.. (2011). Inferring social roles in long timespan video sequence. 1456–1463. 3 indexed citations
17.
Hu, Wenze & Song‐Chun Zhu. (2010). Learning a probabilistic model mixing 3D and 2D primitives for view invariant object recognition. 2273–2280. 18 indexed citations
18.
Gong, Haifeng, et al.. (2009). Generative model for abandoned object detection. 853–856. 15 indexed citations
19.
Hu, Wenze, et al.. (2008). An interactive scene annotation tool for video surveillance. Proceedings - International Conference on Pattern Recognition. 1–4.
20.

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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