| Factorial switching linear dynamical systems applied to physiological condition monitoring JA Quinn, CKI Williams, N McIntosh IEEE Transactions on Pattern Analysis and Machine Intelligence 31 (9), 1537-1551, 2008 | 114 | 2008 |
| A comparison of graphical and textual presentations of time series data to support medical decision making in the neonatal intensive care unit AS Law, Y Freer, J Hunter, RH Logie, N Mcintosh, J Quinn Journal of Clinical Monitoring and Computing 19 (3), 183-194, 2005 | 107 | 2005 |
| Deep convolutional neural networks for microscopy-based point of care diagnostics JA Quinn, R Nakasi, PKB Mugagga, P Byanyima, W Lubega, A Andama Machine Learning for Healthcare Conference, 271-281, 2016 | 68 | 2016 |
| Divergence-based classification in learning vector quantization E Mwebaze, P Schneider, FM Schleif, JR Aduwo, JA Quinn, S Haase, ... Neurocomputing 74 (9), 1429-1435, 2011 | 61 | 2011 |
| Factorial Switching Kalman Filters for Condition Monitoring in Neonatal Intensive Care C Williams, J Quinn, N McIntosh Advances in Neural Information Processing Systems 18, 2006 | 52 | 2006 |
| A least-squares approach to anomaly detection in static and sequential data JA Quinn, M Sugiyama Pattern Recognition Letters 40, 36-40, 2014 | 48 | 2014 |
| Known unknowns: Novelty detection in condition monitoring JA Quinn, CKI Williams Iberian Conference on Pattern Recognition and Image Analysis, 1-6, 2007 | 48 | 2007 |
| Location Segmentation, Inference and Prediction for Anticipatory Computing. N Eagle, A Clauset, JA Quinn AAAI Spring Symposium: Technosocial Predictive Analytics, 20-25, 2009 | 40 | 2009 |
| Humanitarian applications of machine learning with remote-sensing data: review and case study in refugee settlement mapping JA Quinn, MM Nyhan, C Navarro, D Coluccia, L Bromley, M Luengo-Oroz Philosophical Transactions of the Royal Society A: Mathematical, Physical …, 2018 | 36 | 2018 |
| Methodologies for continuous cellular tower data analysis N Eagle, JA Quinn, A Clauset International Conference on Pervasive Computing, 342-353, 2009 | 36 | 2009 |
| Automated Blood Smear Analysis for Mobile Malaria Diagnosis JA Quinn, A Andama, I Munabi, FN Kiwanuka Mobile Point-of-Care Monitors and Diagnostic Device Design, 2014 | 32 | 2014 |
| Direct learning of sparse changes in Markov networks by density ratio estimation S Liu, JA Quinn, MU Gutmann, T Suzuki, M Sugiyama Neural computation 26 (6), 1169-1197, 2014 | 30 | 2014 |
| Modeling and monitoring crop disease in developing countries J Quinn, K Leyton-Brown, E Mwebaze Proceedings of the AAAI Conference on Artificial Intelligence 25 (1), 2011 | 29 | 2011 |
| Automated Vision-Based Diagnosis of Cassava Mosaic Disease. JR Aduwo, E Mwebaze, JA Quinn Industrial Conference on Data Mining-Workshops, 114-122, 2010 | 26 | 2010 |
| Traffic Flow Monitoring in Crowded Cities. JA Quinn, R Nakibuule AAAI Spring Symposium: Artificial Intelligence for Development, 2010 | 23 | 2010 |
| Computational sustainability and artificial intelligence in the developing world J Quinn, V Frias-Martinez, L Subramanian AI Magazine 35 (3), 36-47, 2014 | 21 | 2014 |
| Automated Vision-Based Diagnosis of Banana Bacterial Wilt Disease and Black Sigatoka Disease G Owomugisha, JA Quinn, E Mwebaze, J Lwasa The 1st International Conference on the Use of Mobile Information and …, 2014 | 19 | 2014 |
| Bayesian Condition Monitoring in Neonatal Intensive Care J Quinn University of Edinburgh, 2007 | 18 | 2007 |
| Very Low Resource Radio Browsing for Agile Developmental and Humanitarian Monitoring. A Saeb, R Menon, H Cameron, W Kibira, J Quinn, T Niesler INTERSPEECH, 2118-2122, 2017 | 14 | 2017 |
| A mobile market for agricultural trade in Uganda R Ssekibuule, JA Quinn, K Leyton-Brown Proceedings of the 4th Annual Symposium on Computing for Development, 1-10, 2013 | 14 | 2013 |
Ernest Tonny MwebazeResearch ScientistAdresse e-mail validée de sunbird.ai
