Soft+ hardwired attention: An lstm framework for human trajectory prediction and abnormal event detection T Fernando, S Denman, S Sridharan, C Fookes Neural networks 108, 466-478, 2018 | 376 | 2018 |
Crowd counting using multiple local features D Ryan, S Denman, C Fookes, S Sridharan 2009 digital image computing: techniques and applications, 81-88, 2009 | 372 | 2009 |
Deep learning for medical anomaly detection–a survey T Fernando, H Gammulle, S Denman, S Sridharan, C Fookes ACM Computing Surveys (CSUR) 54 (7), 1-37, 2021 | 221 | 2021 |
Two stream lstm: A deep fusion framework for human action recognition H Gammulle, S Denman, S Sridharan, C Fookes 2017 IEEE winter conference on applications of computer vision (WACV), 177-186, 2017 | 211 | 2017 |
Gait energy volumes and frontal gait recognition using depth images S Sivapalan, D Chen, S Denman, S Sridharan, C Fookes 2011 International Joint Conference on Biometrics (IJCB), 1-6, 2011 | 186 | 2011 |
A database for person re-identification in multi-camera surveillance networks A Bialkowski, S Denman, S Sridharan, C Fookes, P Lucey Digital Image Computing Techniques and Applications (DICTA), 2012 …, 2012 | 180 | 2012 |
Graph-based deep learning for medical diagnosis and analysis: past, present and future D Ahmedt-Aristizabal, MA Armin, S Denman, C Fookes, L Petersson Sensors 21 (14), 4758, 2021 | 179 | 2021 |
A mask-based approach for the geometric calibration of thermal-infrared cameras S Vidas, R Lakemond, S Denman, C Fookes, S Sridharan, T Wark IEEE Transactions on Instrumentation and Measurement 61 (6), 1625-1635, 2012 | 173 | 2012 |
An evaluation of crowd counting methods, features and regression models D Ryan, S Denman, S Sridharan, C Fookes Computer Vision and Image Understanding 130, 1-17, 2015 | 159 | 2015 |
Textures of optical flow for real-time anomaly detection in crowds D Ryan, S Denman, C Fookes, S Sridharan 2011 8th IEEE international conference on advanced video and signal based …, 2011 | 133 | 2011 |
An adaptive optical flow technique for person tracking systems S Denman, V Chandran, S Sridharan Pattern recognition letters 28 (10), 1232-1239, 2007 | 121 | 2007 |
Deep learning for patient-independent epileptic seizure prediction using scalp EEG signals T Dissanayake, T Fernando, S Denman, S Sridharan, C Fookes IEEE Sensors Journal 21 (7), 9377-9388, 2021 | 109 | 2021 |
Improved simultaneous computation of motion detection and optical flow for object tracking S Denman, C Fookes, S Sridharan 2009 Digital Image Computing: Techniques and Applications, 175-182, 2009 | 104 | 2009 |
A survey on graph-based deep learning for computational histopathology D Ahmedt-Aristizabal, MA Armin, S Denman, C Fookes, L Petersson Computerized Medical Imaging and Graphics 95, 102027, 2022 | 102 | 2022 |
Predicting the future: A jointly learnt model for action anticipation H Gammulle, S Denman, S Sridharan, C Fookes Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2019 | 101 | 2019 |
Fruit Quantity and Ripeness Estimation Using a Robotic Vision System M Halstead, C McCool, S Denman, T Perez, C Fookes IEEE Robotics and Automation Letters 3 (4), 2995-3002, 2018 | 99 | 2018 |
Automated detection of koalas using low-level aerial surveillance and machine learning E Corcoran, S Denman, J Hanger, B Wilson, G Hamilton Scientific reports 9 (1), 3208, 2019 | 96 | 2019 |
Using synthetic data to improve facial expression analysis with 3d convolutional networks I Abbasnejad, S Sridharan, D Nguyen, S Denman, C Fookes, S Lucey Proceedings of the IEEE International Conference on Computer Vision …, 2017 | 87 | 2017 |
Tracking by prediction: A deep generative model for mutli-person localisation and tracking T Fernando, S Denman, S Sridharan, C Fookes 2018 IEEE Winter conference on applications of computer vision (WACV), 1122-1132, 2018 | 83 | 2018 |
Soft-biometrics: unconstrained authentication in a surveillance environment S Denman, C Fookes, A Bialkowski, S Sridharan 2009 Digital Image Computing: Techniques and Applications, 196-203, 2009 | 82 | 2009 |