Simon Denman

7.4k citations

203 papers · 5.5k · 2 hit papers · h-index 40

Impact in

Computer Vision and Pattern Recognition top 0.2%
- Video Surveillance and Tracking Methods
- Human Pose and Action Recognition
- Advanced Neural Network Applications
Signal Processing top 2%

Papers in

Computer Vision and Pattern Recognition 128
- Video Surveillance and Tracking Methods 70
- Human Pose and Action Recognition 25
- Advanced Image and Video Retrieval Techniques 12
- Face recognition and analysis 10
- Image Retrieval and Classification Techniques 8
Artificial Intelligence 35
- Anomaly Detection Techniques and Applications 15

Co-authors: Clinton Fookes (172 shared papers)Sridha Sridharan (159 shared papers)Tharindu Fernando (39 shared papers)Harshala Gammulle (14 shared papers)David Ryan (15 shared papers)David Ahmedt‐Aristizabal (22 shared papers)Kien Nguyen (14 shared papers)Lars Petersson (9 shared papers)
Journals: Computer Vision and Image Understanding (6 papers)Pattern Recognition (5 papers)IEEE Journal of Biomedical and Health Informatics (5 papers)Pattern Recognition Letters (5 papers)Expert Systems with Applications (4 papers)
Partner nations: Australia United States Germany

In The Last Decade

Simon Denman

196 papers receiving 5.3k citations

Simon Denman's Hit Papers

align trajectories log scale

Deep Learning for Medical Anomaly Detection – A Survey 2021 · 253 citations

What are hit papers?

Paper score: A paper's citations measured against the top-1% bar of its own field and year: the square root of citations ÷ bar, so 1 means right at the bar and 2 means four times its citations. The bar blends the citation counts that enter the top 1% of the paper's subfields in its year (weighted 89.5%), of those subfields over all years (0.5%) and of its year across all fields (10%); a subfield and year with fewer than 400 papers takes its year's bar. Papers from 2026 are not scored yet: in an unfinished year, when a paper appeared matters more than how it is cited.

Hit paper: A paper cited at least 1.5× the top-1% bar of its field and year: a paper score of at least √1.5.

2021 ACM Computing Surveys
2018 Neural Networks

Peers

Countries citing papers authored by Simon Denman

Since Specialization

Citations

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

Fields of papers citing papers by Simon Denman

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Simon Denman, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Simon Denman Line = papers co-authored together Simon Denman links everyone, so they are left out of the graph.

All Works

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20 of 20 papers shown

Showing the 20 most-cited of 203 papers — load more, or switch the sort, to bring in the rest.

#	Work
1	Soft + Hardwired attention: An LSTM framework for human trajectory prediction and abnormal event detection Neural Networks ·Tharindu Fernando, Simon Denman, Sridha Sridharan, Clinton Fookes Hit paper breakdown →	2018	300
2	Crowd Counting Using Multiple Local Features Digital Image Computing: Techniques and Applications ·David Ryan, Simon Denman, Clinton Fookes, Sridha Sridharan	2009	254
3	Deep Learning for Medical Anomaly Detection – A Survey ACM Computing Surveys ·Tharindu Fernando, Harshala Gammulle, Simon Denman, Sridha Sridharan, Clinton Fookes Hit paper breakdown →	2021	253
4	Graph-Based Deep Learning for Medical Diagnosis and Analysis: Past, Present and Future Sensors ·David Ahmedt‐Aristizabal, Mohammad Ali Armin, Simon Denman, Clinton Fookes, Lars Petersson	2021	179
5	Two Stream LSTM: A Deep Fusion Framework for Human Action Recognition IEEE Winter Conference on Applications of Computer Vision ·Harshala Gammulle, Simon Denman, Sridha Sridharan, Clinton Fookes	2017	143
6	Deep Learning for Patient-Independent Epileptic Seizure Prediction Using Scalp EEG Signals IEEE Sensors Journal ·Theekshana Dissanayake, Tharindu Fernando, Simon Denman, Sridha Sridharan, Clinton Fookes	2021	138
7	Gait energy volumes and frontal gait recognition using depth images QUT ePrints (Queensland University of Technology) ·Sabesan Sivapalan, Daniel Chen, Simon Denman, Sridha Sridharan, Clinton Fookes	2011	128
8	A Mask-Based Approach for the Geometric Calibration of Thermal-Infrared Cameras IEEE Transactions on Instrumentation and Measurement ·Stephen Vidas, Ruan Lakemond, Simon Denman, Clinton Fookes, Sridha Sridharan, Tim Wark	2012	119
9	Fruit Quantity and Ripeness Estimation Using a Robotic Vision System IEEE Robotics and Automation Letters ·Michael Halstead, Chris McCool, Simon Denman, Tristán Pérez, Clinton Fookes	2018	108
10	A Database for Person Re-Identification in Multi-Camera Surveillance Networks International Conference on Digital Image Computing: Techniques and Applications (DICTA) ·Alina Bialkowski, Simon Denman, Sridha Sridharan, Clinton Fookes, Patrick Lucey	2012	107
11	An evaluation of crowd counting methods, features and regression models Computer Vision and Image Understanding ·David Ryan, Simon Denman, Sridha Sridharan, Clinton Fookes	2014	107
12	Geometric Deep Learning for Subject Independent Epileptic Seizure Prediction Using Scalp EEG Signals IEEE Journal of Biomedical and Health Informatics ·Theekshana Dissanayake, Tharindu Fernando, Simon Denman, Sridha Sridharan, Clinton Fookes	2021	99
13	A survey on graph-based deep learning for computational histopathology Computerized Medical Imaging and Graphics ·David Ahmedt‐Aristizabal, Mohammad Ali Armin, Simon Denman, Clinton Fookes, Lars Petersson	2021	97
14	A Robust Interpretable Deep Learning Classifier for Heart Anomaly Detection Without Segmentation IEEE Journal of Biomedical and Health Informatics ·Theekshana Dissanayake, Tharindu Fernando, Simon Denman, Sridha Sridharan, Houman Ghaemmaghami, Clinton Fookes	2020	84
15	Textures of optical flow for real-time anomaly detection in crowds IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS) ·David Ryan, Simon Denman, Clinton Fookes, Sridha Sridharan	2011	80
16	Automated detection of koalas using low-level aerial surveillance and machine learning Scientific Reports ·Evangeline Mae Corcoran, Simon Denman, Jon J. Hanger, Grant S. Hamilton +1 other	2019	80
17	Identification of Children at Risk of Schizophrenia via Deep Learning and EEG Responses IEEE Journal of Biomedical and Health Informatics ·David Ahmedt‐Aristizabal, Tharindu Fernando, Simon Denman, Jonathan Robinson, Sridha Sridharan, Patrick Johnston, Kristin R. Laurens, Clinton Fookes	2020	79
18	An adaptive optical flow technique for person tracking systems Pattern Recognition Letters ·Simon Denman, Vinod Chandran, Sridha Sridharan	2007	69
19	Heart Sound Segmentation using Bidirectional LSTMs with Attention QUT ePrints (Queensland University of Technology) ·Houman Ghaemmaghami, Simon Denman, Sridha Sridharan, Nayyar Hussain, Clinton Fookes +1 other	2020	65
20	Deep Inverse Reinforcement Learning for Behavior Prediction in Autonomous Driving: Accurate Forecasts of Vehicle Motion IEEE Signal Processing Magazine ·Tharindu Fernando, Simon Denman, Sridha Sridharan, Clinton Fookes	2020	65

About Simon Denman

Simon Denman is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Signal Processing, Cognitive Neuroscience and Experimental and Cognitive Psychology, having authored 203 papers that have together received 5.5k indexed citations. Recurring topics across this work include Video Surveillance and Tracking Methods (70 papers), Human Pose and Action Recognition (25 papers), Anomaly Detection Techniques and Applications (15 papers), EEG and Brain-Computer Interfaces (13 papers), Advanced Image and Video Retrieval Techniques (12 papers), Face recognition and analysis (10 papers), Emotion and Mood Recognition (9 papers) and Image Retrieval and Classification Techniques (8 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (2.5k citations), Signal Processing (289 citations), Automotive Engineering (312 citations), Cognitive Neuroscience (578 citations) and Artificial Intelligence (897 citations). Simon Denman has collaborated with scholars based in Australia, United States and Germany. Frequent co-authors include Clinton Fookes, Sridha Sridharan, Tharindu Fernando, Harshala Gammulle, David Ryan, David Ahmedt‐Aristizabal, Kien Nguyen, Lars Petersson, Mohammad Ali Armin and Theekshana Dissanayake. Their work appears in journals such as Computer Vision and Image Understanding, Pattern Recognition, IEEE Journal of Biomedical and Health Informatics, Pattern Recognition Letters and Expert Systems with Applications.

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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Simon Denman's Hit Papers

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About Simon Denman

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