Neil M. Robertson

80 papers receiving 1.5k citations

Peers

Neil M. Robertson
Comparison fields: 5 of 117
  • Computer Vision and Pattern Recognition 1.1k
  • Artificial Intelligence 459
  • Signal Processing 237
  • Biomedical Engineering 147
  • Computer Networks and Communications 132
Replace Gunther Heidemann with:
Gunther Heidemann Germany
Zhonglong Zheng China
Xi Zhou China
Vineeth N Balasubramanian India
Yuanlong Yu China
Qing Guo China
Shohreh Kasaei Iran
Byung Cheol Song South Korea
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Neil M. Robertson relative to Gunther Heidemann Germany Gunther Heidemann's profile →
Citations per field
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Citations per year

Countries citing papers authored by Neil M. Robertson

Since Specialization
Citations

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

Fields of papers citing papers by Neil M. Robertson

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Neil M. Robertson. 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 Neil M. Robertson. The network helps show where Neil M. Robertson may publish in the future.

Co-authorship network of co-authors of Neil M. Robertson

This figure shows the co-authorship network connecting the top 25 collaborators of Neil M. Robertson. A scholar is included among the top collaborators of Neil M. Robertson 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 Neil M. Robertson. Neil M. Robertson 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
#WorkIndexed citations
1
ProSelfLC: Progressive Self Label Correction for Target Revising in Label Noise.
1
2 13
3 94
4 126
5
Improved Mean Absolute Error for Learning Meaningful Patterns from Abnormal Training Data
7
6
Derivative Manipulation For Adjusting Emphasis Density Function: A General Example Weighting Framework
1
7 150
8
Improving MAE against CCE under Label Noise.
6
9
Emphasis Regularisation by Gradient Rescaling for Training Deep Neural Networks with Noisy Labels.
4
10 7
11 23
12 56
13 17
14
Identifying anomalous objects in SAS imagery using uncertainty
1
15 2
16
Height approximation for audio source localisation and tracking
1
17 17
18 17
19 4
20 39

About Neil M. Robertson

Neil M. Robertson is a scholar working on Computer Vision and Pattern Recognition, Computational Mathematics and Artificial Intelligence, having authored 81 papers that have together received 1.6k indexed citations. Recurring topics across this work include Video Surveillance and Tracking Methods (23 papers), Human Pose and Action Recognition (21 papers) and Anomaly Detection Techniques and Applications (16 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (1.1k citations), Signal Processing (237 citations) and Human-Computer Interaction (104 citations). Neil M. Robertson has collaborated with scholars based in United Kingdom, China and Malaysia. Frequent co-authors include Ian Reid, Hua Yang, Sankha Mukherjee, Guosheng Hu, Elyor Kodirov, Jialie Shen, James R. Hopgood, Xinshao Wang, John Thompson and Romain Garnier. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Image Processing and IEEE Transactions on Signal Processing.

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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