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Isabel M J Sargent
Isabel M J Sargent
Ordnance Survey; University of Southampton; UCL
Verified email at os.uk
Title
Cited by
Cited by
Year
An object-based convolutional neural network (OCNN) for urban land use classification
C Zhang, I Sargent, X Pan, H Li, A Gardiner, J Hare, PM Atkinson
Remote sensing of environment 216, 57-70, 2018
4122018
Joint Deep Learning for land cover and land use classification
C Zhang, I Sargent, X Pan, H Li, A Gardiner, J Hare, PM Atkinson
Remote sensing of environment 221, 173-187, 2019
3862019
A hybrid MLP-CNN classifier for very fine resolution remotely sensed image classification
C Zhang, X Pan, H Li, A Gardiner, I Sargent, J Hare, PM Atkinson
ISPRS Journal of Photogrammetry and Remote Sensing 140, 133-144, 2018
3732018
Scale Sequence Joint Deep Learning (SS-JDL) for land use and land cover classification
C Zhang, PA Harrison, X Pan, H Li, I Sargent, PM Atkinson
Remote Sensing of Environment 237, 111593, 2020
912020
VPRS-based regional decision fusion of CNN and MRF classifications for very fine resolution remotely sensed images
C Zhang, I Sargent, X Pan, A Gardiner, J Hare, PM Atkinson
IEEE Transactions on Geoscience and Remote Sensing 56 (8), 4507-4521, 2018
872018
Quality assessment of 3D building data
D Akca, M Freeman, I Sargent, A Gruen
The Photogrammetric Record 25 (132), 339-355, 2010
682010
Data quality in 3D: Gauging quality measures from users’ requirements
I Sargent, J Harding, M Freeman
International Archives of Photogrammetry, Remote Sensing and Spatial …, 2007
362007
Exploring the geostatistical method for estimating the signal-to-noise ratio of images
PM Atkinson, IM Sargent, GM Foody, J Williams
Photogrammetric Engineering & Remote Sensing 73 (7), 841-850, 2007
242007
Interpreting image-based methods for estimating the signal-to-noise ratio
PM Atkinson, IM Sargent, GM Foody, J Williams
International Journal of Remote Sensing 26 (22), 5099-5115, 2005
212005
Joint deep learning for land cover and land use classification
I Sargent, C Zhang, PM Atkinson
US Patent 10,984,532, 2021
132021
Thematic labelling from hyperspectral remotely sensed imagery: trade-offs in image properties
GM Foody, IMJ Sargent, PM Atkinson, JW Williams
International Journal of Remote Sensing 25 (12), 2337-2363, 2004
132004
Object-based convolutional neural network for land use classification
I Sargent, C Zhang, PM Atkinson
US Patent 10,922,589, 2021
92021
Moving towards 3D: from a National Mapping Agency perspective
D Capstick, G Heathcote, J Horgan, I Sargent
The Cartographic Journal 44 (3), 233-238, 2007
92007
Quality assessment of 3D building data by 3D surface matching
D Akca, M Freeman, A Gruen, I Sargent
The International Archives of the Photogr ammetry, Remote Sensing and …, 2008
82008
Topographic data machine learning method and system
I Sargent, J Hare
US Patent 10,586,103, 2020
72020
Fast quality control of 3D city models
D Akca, A Gruen, M Freeman, I Sargent
The International LIDAR Mapping Forum, New Orleans, Louisiana, USA, January …, 2009
72009
Quantifying and visualising the uncertainty in 3D building model walls using terrestrial lidar data
M Freeman, I Sargent
Proc. of the Remote Sensing and Photogrammetry Society Conference, 15-17.9, 2008
72008
SAR imagery for flood monitoring and assessment
P Aplin, PM Atkinson, AR Tatnall, ME Cutler, I Sargent
Remote Sensing Society, 1999
71999
The building blocks of user-focused 3D city models
I Sargent, D Holland, J Harding
ISPRS international journal of geo-information 4 (4), 2890-2904, 2015
62015
Opportunities for machine learning and artificial intelligence in national mapping agencies: enhancing ordnance survey workflow
J Murray, I Sargent, D Holland, A Gardiner, K Dionysopoulou, S Coupland, ...
The International Archives of the Photogrammetry, Remote Sensing and Spatial …, 2020
52020
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