Philip Ogunbona

5.7k total citations · 1 hit paper
125 papers, 3.2k citations indexed

About

Philip Ogunbona is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Biomedical Engineering. According to data from OpenAlex, Philip Ogunbona has authored 125 papers receiving a total of 3.2k indexed citations (citations by other indexed papers that have themselves been cited), including 94 papers in Computer Vision and Pattern Recognition, 24 papers in Artificial Intelligence and 22 papers in Biomedical Engineering. Recurrent topics in Philip Ogunbona's work include Human Pose and Action Recognition (26 papers), Image Retrieval and Classification Techniques (18 papers) and Advanced Data Compression Techniques (17 papers). Philip Ogunbona is often cited by papers focused on Human Pose and Action Recognition (26 papers), Image Retrieval and Classification Techniques (18 papers) and Advanced Data Compression Techniques (17 papers). Philip Ogunbona collaborates with scholars based in Australia, China and United States. Philip Ogunbona's co-authors include Wanqing Li, Jing Zhang, Pichao Wang, Chang Tang, Duc Thanh Nguyen, Zhimin Gao, Vu Minh Hieu Phan, Sérgio Escalera, Jun Wan and Lei Wang and has published in prestigious journals such as SHILAP Revista de lepidopterología, IEEE Transactions on Pattern Analysis and Machine Intelligence and Applied Energy.

In The Last Decade

Philip Ogunbona

117 papers receiving 3.1k citations

Hit Papers

Joint Geometrical and Statistical Alignment for Visual Do... 2017 2026 2020 2023 2017 100 200 300 400

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Philip Ogunbona Australia 29 2.2k 1.1k 689 534 231 125 3.2k
Greg Mori Canada 34 3.2k 1.4× 1.6k 1.4× 642 0.9× 353 0.7× 107 0.5× 102 4.0k
Ahmad Jalal Pakistan 41 3.4k 1.5× 1.2k 1.1× 880 1.3× 506 0.9× 268 1.2× 78 4.3k
Christopher R. Wren United States 11 3.0k 1.4× 475 0.4× 286 0.4× 460 0.9× 268 1.2× 21 3.3k
Xiaopeng Hong China 35 3.3k 1.5× 1.7k 1.6× 630 0.9× 425 0.8× 139 0.6× 146 4.8k
A. Azarbayejani United States 11 3.6k 1.6× 484 0.4× 333 0.5× 591 1.1× 297 1.3× 25 4.1k
Zhang Zhang China 23 2.6k 1.2× 894 0.8× 895 1.3× 274 0.5× 338 1.5× 85 3.9k
Lisa Anne Hendricks United States 16 3.6k 1.6× 2.0k 1.8× 606 0.9× 373 0.7× 190 0.8× 28 5.1k
Daijin Kim South Korea 34 2.9k 1.3× 1.0k 1.0× 412 0.6× 344 0.6× 348 1.5× 179 4.2k
Ahmad Jalal Pakistan 36 2.6k 1.2× 888 0.8× 645 0.9× 331 0.6× 203 0.9× 115 3.6k
Sanketh Shetty France 4 3.7k 1.6× 2.0k 1.9× 760 1.1× 444 0.8× 196 0.8× 6 4.8k

Countries citing papers authored by Philip Ogunbona

Since Specialization
Citations

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

Fields of papers citing papers by Philip Ogunbona

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Philip Ogunbona

This figure shows the co-authorship network connecting the top 25 collaborators of Philip Ogunbona. A scholar is included among the top collaborators of Philip Ogunbona 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 Philip Ogunbona. Philip Ogunbona 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.
Li, Wanqing, et al.. (2024). Asynchronous Joint-Based Temporal Pooling for Skeleton-Based Action Recognition. IEEE Transactions on Circuits and Systems for Video Technology. 35(1). 357–366. 3 indexed citations
2.
Phan, Vu Minh Hieu & Philip Ogunbona. (2020). Modelling Context and Syntactical Features for Aspect-based Sentiment Analysis. 3211–3220. 131 indexed citations
3.
Wang, Huiquan, Zhe Zhao, Xing Feng, et al.. (2020). Fluorescence Molecular Tomography Reconstruction of Small Targets Using Stacked Auto-Encoder Neural Networks. IEEE Access. 8. 37657–37663. 15 indexed citations
4.
Zhang, Jing, Wanqing Li, Philip Ogunbona, & Dong Xu. (2019). Recent Advances in Transfer Learning for Cross-Dataset Visual Recognition. ACM Computing Surveys. 52(1). 1–38. 60 indexed citations
5.
Wang, Pichao, Wanqing Li, Zhimin Gao, Chang Tang, & Philip Ogunbona. (2018). Depth Pooling Based Large-Scale 3-D Action Recognition With Convolutional Neural Networks. IEEE Transactions on Multimedia. 20(5). 1051–1061. 136 indexed citations
6.
Zhang, Jing, Wanqing Li, & Philip Ogunbona. (2017). Transfer Learning for Cross-Dataset Recognition: A Survey. arXiv (Cornell University). 21 indexed citations
7.
Li, Wanqing, et al.. (2017). Cross-Dataset Recognition: A Survey.. arXiv (Cornell University). 1 indexed citations
8.
Xiao, Zhitao, Lei Geng, Fang Zhang, et al.. (2017). Automatic non-proliferative diabetic retinopathy screening system based on color fundus image. BioMedical Engineering OnLine. 16(1). 122–122. 30 indexed citations
9.
Sharma, Rajeev, et al.. (2014). Estimating the magnitude of method bias on account of text similarity using a natural language processing-based technique. Journal of the Association for Information Systems. 1 indexed citations
10.
Ogunbona, Philip, et al.. (2013). Pathological Gait Detection of Parkinson's Disease Using Sparse Representation. 1–8. 21 indexed citations
11.
Zhong, Yuan, Lei Ye, Wanqing Li, & Philip Ogunbona. (2007). Perceived Similarity and Visual Descriptions in Content-Based Image Retrieval. 173–180.
12.
Li, Wanqing, et al.. (2006). Facial expression recognition for multiplayer online games. 52–58. 11 indexed citations
13.
Ye, Lei, Philip Ogunbona, & Jianqiang Wang. (2006). Image Content Annotation Based on Visual Features. 1614. 62–69. 4 indexed citations
14.
Safavi–Naini, Reihaneh, et al.. (2005). High-capacity steganography using a shared colour palette. IEE Proceedings - Vision Image and Signal Processing. 152(6). 787–787. 4 indexed citations
15.
Li, Wanqing, et al.. (2005). A new QIM-based image watermarking method and system. Research Online (University of Wollongong). 160–164. 3 indexed citations
16.
Sheppard, Nicholas Paul, Reihaneh Safavi–Naini, & Philip Ogunbona. (2002). Digital watermarks for copyright protection. Research Online (University of Wollongong). 12(1). 110–130. 6 indexed citations
17.
Ogunbona, Philip, et al.. (2002). Compact feature vector for natural texture classification. 36. 59–63.
18.
Kakarala, Ramakrishna & Philip Ogunbona. (2001). Signal analysis using a multiresolution form of the singular value decomposition. IEEE Transactions on Image Processing. 10(5). 724–735. 93 indexed citations
19.
Shanbehzadeh, Jamshid & Philip Ogunbona. (1997). On the computational complexity of the LBG and PNN algorithms. IEEE Transactions on Image Processing. 6(4). 614–616. 33 indexed citations
20.
Shanbehzadeh, Jamshid & Philip Ogunbona. (1997). Index-compressed vector quantisation based on index mapping. IEE Proceedings - Vision Image and Signal Processing. 144(1). 31–31. 10 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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