| Cattle behaviour classification from collar, halter, and ear tag sensors A Rahman, DV Smith, B Little, AB Ingham, PL Greenwood, ... Information processing in agriculture 5 (1), 124-133, 2018 | 183 | 2018 |
| Efficient orthogonal parametrisation of recurrent neural networks using householder reflections Z Mhammedi, A Hellicar, A Rahman, J Bailey International Conference on Machine Learning, 2401-2409, 2017 | 170 | 2017 |
| Behavior classification of cows fitted with motion collars: Decomposing multi-class classification into a set of binary problems D Smith, A Rahman, GJ Bishop-Hurley, J Hills, S Shahriar, D Henry, ... Computers and Electronics in Agriculture 131, 40-50, 2016 | 141 | 2016 |
| Resource Allocation and Service Provisioning in Multi-Agent Cloud Robotics: A Comprehensive Survey M Afrin, J Jin, A Rahman, A Rahman, J Wan, E Hossain IEEE Communications Surveys & Tutorials, 2021 | 138 | 2021 |
| Detecting heat events in dairy cows using accelerometers and unsupervised learning MS Shahriar, D Smith, A Rahman, M Freeman, J Hills, R Rawnsley, ... Computers and Electronics in Agriculture 128, 20-26, 2016 | 126 | 2016 |
| Multi-objective resource allocation for Edge Cloud based robotic workflow in smart factory M Afrin, J Jin, A Rahman, YC Tian, A Kulkarni Future Generation Computer Systems 97, 119-130, 2019 | 125 | 2019 |
| Cluster-oriented ensemble classifier: Impact of multicluster characterization on ensemble classifier learning B Verma, A Rahman IEEE Transactions on knowledge and data engineering 24 (4), 605-618, 2011 | 121 | 2011 |
| HazeEst: machine learning based metropolitan air pollution estimation from fixed and mobile sensors K Hu, A Rahman, H Bhrugubanda, V Sivaraman IEEE Sensors Journal 17 (11), 3517-3525, 2017 | 118 | 2017 |
| Novel layered clustering-based approach for generating ensemble of classifiers A Rahman, B Verma IEEE Transactions on Neural Networks 22 (5), 781-792, 2011 | 111 | 2011 |
| Design and evaluation of a metropolitan air pollution sensing system K Hu, V Sivaraman, BG Luxan, A Rahman IEEE Sensors Journal 16 (5), 1448-1459, 2015 | 106 | 2015 |
| Multiple steps ahead solar photovoltaic power forecasting based on univariate machine learning models and data re-sampling M Rana, A Rahman Sustainable Energy, Grids and Networks 21, 100286, 2020 | 97 | 2020 |
| Use of sensor-determined behaviours to develop algorithms for pasture intake by individual grazing cattle PL Greenwood, DR Paull, J McNally, T Kalinowski, D Ebert, B Little, ... Crop and Pasture Science 68 (12), 1091-1099, 2017 | 79 | 2017 |
| Ensemble classifier generation using non-uniform layered clustering and Genetic Algorithm A Rahman, B Verma Knowledge-Based Systems 43, 30-42, 2013 | 72 | 2013 |
| Robust malware defense in industrial IoT applications using machine learning with selective adversarial samples ME Khoda, T Imam, J Kamruzzaman, I Gondal, A Rahman IEEE Transactions on Industry Applications 56 (4), 4415-4424, 2019 | 63 | 2019 |
| Dissolved oxygen prediction in prawn ponds from a group of one step predictors A Rahman, J Dabrowski, J McCulloch Information Processing in Agriculture 7 (2), 307-317, 2020 | 62 | 2020 |
| Communication-aware cloud robotic task offloading with on-demand mobility for smart factory maintenance A Rahman, J Jin, AL Cricenti, A Rahman, A Kulkarni IEEE Transactions on Industrial Informatics 15 (5), 2500-2511, 2018 | 61 | 2018 |
| ForecastNet: a time-variant deep feed-forward neural network architecture for multi-step-ahead time-series forecasting JJ Dabrowski, YF Zhang, A Rahman Neural Information Processing: 27th International Conference, ICONIP 2020 …, 2020 | 53 | 2020 |
| An image based approach to compute object distance A Rahman, A Salam, M Islam, P Sarker International Journal of Computational Intelligence Systems 1 (4), 304-312, 2008 | 48 | 2008 |
| Wind power prediction in new stations based on knowledge of existing Stations: A cluster based multi source domain adaptation approach S Tasnim, A Rahman, AMT Oo, ME Haque Knowledge-Based Systems 145, 15-24, 2018 | 47 | 2018 |
| A comparison of autoencoder and statistical features for cattle behaviour classification A Rahman, D Smith, J Hills, G Bishop-Hurley, D Henry, R Rawnsley 2016 international joint conference on neural networks (IJCNN), 2954-2960, 2016 | 46 | 2016 |
Daniel SmithCommonwealth Science and Industrial Research Organisation (CSIRO)E-mail megerősítve itt: csiro.au