Mark R. Pickering

4.3k total citations
244 papers, 3.1k citations indexed

About

Mark R. Pickering is a scholar working on Computer Vision and Pattern Recognition, Biomedical Engineering and Media Technology. According to data from OpenAlex, Mark R. Pickering has authored 244 papers receiving a total of 3.1k indexed citations (citations by other indexed papers that have themselves been cited), including 151 papers in Computer Vision and Pattern Recognition, 55 papers in Biomedical Engineering and 53 papers in Media Technology. Recurrent topics in Mark R. Pickering's work include Advanced Vision and Imaging (49 papers), Video Coding and Compression Technologies (45 papers) and Advanced Data Compression Techniques (33 papers). Mark R. Pickering is often cited by papers focused on Advanced Vision and Imaging (49 papers), Video Coding and Compression Technologies (45 papers) and Advanced Data Compression Techniques (33 papers). Mark R. Pickering collaborates with scholars based in Australia, United States and China. Mark R. Pickering's co-authors include Md. Asikuzzaman, Xiuping Jia, Michael R. Frater, Andrew Lambert, J.F. Arnold, Meng Xu, Md. Jahangir Alam, Paul N. Smith, Jennie M. Scarvell and Abdullah Al Muhit and has published in prestigious journals such as SHILAP Revista de lepidopterología, PEDIATRICS and Cochrane Database of Systematic Reviews.

In The Last Decade

Mark R. Pickering

231 papers receiving 3.0k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Mark R. Pickering Australia 26 1.8k 616 539 331 211 244 3.1k
Peter H. N. de With Netherlands 27 2.0k 1.1× 276 0.4× 536 1.0× 429 1.3× 131 0.6× 396 3.6k
Zhu Li China 32 2.7k 1.5× 520 0.8× 643 1.2× 239 0.7× 220 1.0× 306 4.2k
Pau‐Choo Chung Taiwan 27 1.4k 0.8× 309 0.5× 186 0.3× 329 1.0× 139 0.7× 157 2.8k
Michael Rubinstein United States 28 2.9k 1.6× 472 0.8× 627 1.2× 932 2.8× 379 1.8× 64 5.1k
J.H. Husøy Norway 13 1.5k 0.8× 440 0.7× 445 0.8× 278 0.8× 90 0.4× 39 2.4k
Robyn Owens Australia 29 2.8k 1.6× 451 0.7× 485 0.9× 155 0.5× 76 0.4× 89 4.3k
Rangachar Kasturi United States 31 3.7k 2.1× 643 1.0× 558 1.0× 204 0.6× 302 1.4× 149 5.0k
Ning Jia China 14 1.7k 1.0× 265 0.4× 141 0.3× 428 1.3× 135 0.6× 54 2.9k
Jayanta Mukherjee India 22 1.1k 0.6× 230 0.4× 207 0.4× 322 1.0× 140 0.7× 144 1.7k
Kui Jiang China 28 3.3k 1.8× 1.7k 2.8× 157 0.3× 181 0.5× 137 0.6× 170 4.3k

Countries citing papers authored by Mark R. Pickering

Since Specialization
Citations

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

Fields of papers citing papers by Mark R. Pickering

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Mark R. Pickering. 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 Mark R. Pickering. The network helps show where Mark R. Pickering may publish in the future.

Co-authorship network of co-authors of Mark R. Pickering

This figure shows the co-authorship network connecting the top 25 collaborators of Mark R. Pickering. A scholar is included among the top collaborators of Mark R. Pickering 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 Mark R. Pickering. Mark R. Pickering 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.
Perriman, Diana M., et al.. (2024). Shape modelling reveals age‐related knee bony shape changes in asymptomatic knees. Journal of Orthopaedic Research®. 42(11). 2507–2513. 1 indexed citations
2.
Asikuzzaman, Md., et al.. (2022). Blind Camcording-Resistant Video Watermarking in the DTCWT and SVD Domain. IEEE Access. 10. 15681–15698. 13 indexed citations
3.
Asikuzzaman, Md., et al.. (2022). Cursive Text Recognition in Natural Scene Images Using Deep Convolutional Recurrent Neural Network. IEEE Access. 10. 10062–10078. 35 indexed citations
4.
Asikuzzaman, Md., et al.. (2021). A Fast and Robust Framework for 3D/2D Model to Multi-Frame Fluoroscopy Registration. IEEE Access. 9. 134223–134239. 1 indexed citations
5.
Asikuzzaman, Md., et al.. (2020). Stereo Vision-Based 3D Positioning and Tracking. IEEE Access. 8. 138771–138787. 16 indexed citations
6.
Asikuzzaman, Md., et al.. (2020). Cursive-Text: A Comprehensive Dataset for End-to-End Urdu Text Recognition in Natural Scene Images. SHILAP Revista de lepidopterología. 31. 105749–105749. 15 indexed citations
7.
Asikuzzaman, Md., et al.. (2020). Camcording-Resistant Forensic Watermarking Fallback System Using Secondary Watermark Signal. IEEE Transactions on Circuits and Systems for Video Technology. 31(9). 3403–3416. 13 indexed citations
8.
Asikuzzaman, Md., et al.. (2020). Cursive Character Recognition in Natural Scene Images Using a Multilevel Convolutional Neural Network Fusion. IEEE Access. 8. 109054–109070. 24 indexed citations
9.
Asikuzzaman, Md., et al.. (2020). A Deformable 3D-3D Registration Framework Using Discrete Periodic Spline Wavelet and Edge Position Difference. IEEE Access. 8. 146116–146133. 3 indexed citations
10.
Pickering, Mark R., et al.. (2019). An Efficient Image Registration Method for 3D Post-Operative Analysis of Total Knee Arthroplasty. 9(4). 65. 1 indexed citations
11.
Asikuzzaman, Md. & Mark R. Pickering. (2017). An Overview of Digital Video Watermarking. IEEE Transactions on Circuits and Systems for Video Technology. 28(9). 2131–2153. 204 indexed citations
12.
Aktar, Mst. Nargis, et al.. (2017). Segmentation and reconstruction of cervical muscles using knowledge-based grouping adaptation and new step-wise registration with discrete cosines. Computer Methods in Biomechanics and Biomedical Engineering Imaging & Visualization. 7(1). 12–25. 8 indexed citations
13.
Asikuzzaman, Md., Md. Jahangir Alam, Andrew Lambert, & Mark R. Pickering. (2016). Robust DT CWT-Based DIBR 3D Video Watermarking Using Chrominance Embedding. IEEE Transactions on Multimedia. 18(9). 1733–1748. 68 indexed citations
14.
Pickering, Mark R., et al.. (2016). Multi-slice ultrasound image calibration of an intelligent skin-marker for soft tissue artefact compensation. Journal of Biomechanics. 62. 165–171. 4 indexed citations
15.
Muhit, Abdullah Al, Mark R. Pickering, Jennie M. Scarvell, Tom Ward, & Paul N. Smith. (2013). Image-assisted non-invasive and dynamic biomechanical analysis of human joints. Physics in Medicine and Biology. 58(13). 4679–4702. 18 indexed citations
16.
Pickering, Mark R., et al.. (2012). Computationally efficient global motion estimation using a multi-pass image interpolation algorithm. 349–352. 1 indexed citations
17.
Macdonald, Geraldine, Julian P. T. Higgins, Paul Ramchandani, et al.. (2012). Cognitive‐Behavioural Interventions for Children Who Have Been Sexually Abused: A Systematic Review. Campbell Systematic Reviews. 8(1). 1–111. 18 indexed citations
18.
Haque, M.N., et al.. (2011). A Low-Complexity Image Registration Algorithm for Global Motion Estimation. IEEE Transactions on Circuits and Systems for Video Technology. 22(3). 426–433. 11 indexed citations
19.
20.
Wei, Jianxin, et al.. (2005). Tile-boundary artifact reduction using odd tile size and the low-pass first convention. IEEE Transactions on Image Processing. 14(8). 1033–1042. 4 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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