| Cost-sensitive learning of deep feature representations from imbalanced data SH Khan, M Hayat, M Bennamoun, FA Sohel, R Togneri IEEE transactions on neural networks and learning systems 29 (8), 3573-3587, 2017 | 1084 | 2017 |
| A new representation of skeleton sequences for 3d action recognition Q Ke, M Bennamoun, S An, F Sohel, F Boussaid Proceedings of the IEEE conference on computer vision and pattern …, 2017 | 1000 | 2017 |
| A comprehensive survey of deep learning for image captioning MDZ Hossain, F Sohel, MF Shiratuddin, H Laga ACM Computing Surveys (CsUR) 51 (6), 1-36, 2019 | 933 | 2019 |
| Rotational projection statistics for 3D local surface description and object recognition Y Guo, F Sohel, M Bennamoun, M Lu, J Wan International journal of computer vision 105, 63-86, 2013 | 731 | 2013 |
| 3D object recognition in cluttered scenes with local surface features: A survey Y Guo, M Bennamoun, F Sohel, M Lu, J Wan IEEE transactions on pattern analysis and machine intelligence 36 (11), 2270 …, 2014 | 708 | 2014 |
| A comprehensive performance evaluation of 3D local feature descriptors Y Guo, M Bennamoun, F Sohel, M Lu, J Wan, NM Kwok International Journal of Computer Vision 116, 66-89, 2016 | 661 | 2016 |
| A survey of deep learning techniques for weed detection from images ASMM Hasan, F Sohel, D Diepeveen, H Laga, MGK Jones Computers and Electronics in Agriculture 184, 106067, 2021 | 366 | 2021 |
| Automatic Shadow Detection and Removal from a Single Image SH Khan, M Bennamoun, F Sohel, R Togneri IEEE Transactions on Pattern Analysis and Machine Intelligence 38 (3), 431 - 446, 2016 | 279 | 2016 |
| Learning clip representations for skeleton-based 3D action recognition Q Ke, M Bennamoun, S An, F Sohel, F Boussaid IEEE Transactions on Image Processing 27 (6), 2842-2855, 2018 | 275 | 2018 |
| Skeletonnet: Mining deep part features for 3-d action recognition Q Ke, S An, M Bennamoun, F Sohel, F Boussaid IEEE signal processing letters 24 (6), 731-735, 2017 | 193 | 2017 |
| An accurate and robust range image registration algorithm for 3D object modeling Y Guo, F Sohel, M Bennamoun, J Wan, M Lu ieee transactions on multimedia 16 (5), 1377-1390, 2014 | 173 | 2014 |
| RGB-D object recognition and grasp detection using hierarchical cascaded forests U Asif, M Bennamoun, FA Sohel IEEE Transactions on Robotics 33 (3), 547-564, 2017 | 169 | 2017 |
| Automatic feature learning for robust shadow detection SH Khan, M Bennamoun, F Sohel, R Togneri 2014 IEEE conference on computer vision and pattern recognition, 1939-1946, 2014 | 164 | 2014 |
| Leveraging auxiliary tasks with affinity learning for weakly supervised semantic segmentation L Xu, W Ouyang, M Bennamoun, F Boussaid, F Sohel, D Xu Proceedings of the IEEE/CVF international conference on computer vision …, 2021 | 162 | 2021 |
| A novel local surface feature for 3D object recognition under clutter and occlusion Y Guo, F Sohel, M Bennamoun, J Wan, M Lu Information Sciences 293, 196-213, 2015 | 148 | 2015 |
| Machine learning‐based prediction of heart failure readmission or death: implications of choosing the right model and the right metrics SE Awan, M Bennamoun, F Sohel, FM Sanfilippo, G Dwivedi ESC heart failure 6 (2), 428-435, 2019 | 143 | 2019 |
| NormalNet: A voxel-based CNN for 3D object classification and retrieval C Wang, M Cheng, F Sohel, M Bennamoun, J Li Neurocomputing 323, 139-147, 2019 | 140 | 2019 |
| Machine learning in heart failure: ready for prime time SE Awan, F Sohel, FM Sanfilippo, M Bennamoun, G Dwivedi Current opinion in cardiology 33 (2), 190-195, 2018 | 111 | 2018 |
| An integrated framework for 3-D modeling, object detection, and pose estimation from point-clouds Y Guo, M Bennamoun, F Sohel, M Lu, J Wan IEEE Transactions on Instrumentation and Measurement 64 (3), 683-693, 2014 | 109 | 2014 |
| Computer vision for human–machine interaction Q Ke, J Liu, M Bennamoun, S An, F Sohel, F Boussaid Computer vision for assistive healthcare, 127-145, 2018 | 108 | 2018 |
Mohammed BennamounWinthrop Professor - University of Western AustraliaVerified email at uwa.edu.au
