GraphBPT: An Efficient Hierarchical Data Structure for Image Representation and Probabilistic Inference, International Symposium on Mathematical Morphology and Its Applications to Signal and Image Processing, pp.301-312, 2015. ,
DOI : 10.1007/978-3-319-18720-4_26
URL : https://hal.archives-ouvertes.fr/hal-01168116
Mesh approximation using a volume-based metric, Proceedings. Seventh Pacific Conference on Computer Graphics and Applications (Cat. No.PR00293), pp.292-301, 1999. ,
DOI : 10.1109/PCCGA.1999.803373
Comparison of Pansharpening Algorithms: Outcome of the 2006 GRS-S Data-Fusion Contest, IEEE Transactions on Geoscience and Remote Sensing, vol.45, issue.10, pp.453012-3021, 2007. ,
DOI : 10.1109/TGRS.2007.904923
URL : https://hal.archives-ouvertes.fr/hal-00177641
A survey of classical methods and new trends in pansharpening of multispectral images, EURASIP Journal on Advances in Signal Processing, vol.74, issue.10, p.201179, 2011. ,
DOI : 10.1109/IGARSS.2006.974
How useful is regionbased classification of remote sensing images in a deep learning framework, IEEE Geoscience and Remote Sensing Symposium (IGARSS), pp.5091-5094, 2016. ,
URL : https://hal.archives-ouvertes.fr/hal-01320016
Joint Learning from Earth Observation and OpenStreetMap Data to Get Faster Better Semantic Maps, 2017 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), 2017. ,
DOI : 10.1109/CVPRW.2017.199
URL : https://hal.archives-ouvertes.fr/hal-01523573
Automatic detection of residential buildings using LIDAR data and multispectral imagery, ISPRS Journal of Photogrammetry and Remote Sensing, vol.65, issue.5, pp.457-467, 2010. ,
DOI : 10.1016/j.isprsjprs.2010.06.001
Segnet: A deep convolutional encoder-decoder architecture for robust semantic pixel-wise labelling. arXiv preprint, 2015. ,
DOI : 10.1109/tpami.2016.2644615
Segnet: A deep convolutional encoder-decoder architecture for image segmentation, 2015. ,
Hyperspectral Remote Sensing Data Analysis and Future Challenges, IEEE Geoscience and Remote Sensing Magazine, vol.1, issue.2 ,
DOI : 10.1109/MGRS.2013.2244672
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.386.4587
Neural networks for pattern recognition, 1995. ,
Object based image analysis for remote sensing. ISPRS journal of photogrammetry and remote sensing, pp.2-16, 2010. ,
Relationship Between Hyperspectral Reflectance, Soil Nitrate-Nitrogen, Cotton Leaf Chlorophyll, and Cotton Yield: A Step Toward Precision Agriculture, Journal of Sustainable Agriculture, vol.45, issue.3, pp.5-16, 2003. ,
DOI : 10.1080/00103629409369002
A pliant method for anisotropic mesh generation, 5th Intl. Meshing Roundtable, pp.63-74, 1996. ,
Polygon mesh processing, 2010. ,
DOI : 10.1201/b10688
URL : https://hal.archives-ouvertes.fr/inria-00538098
A theoretical analysis of feature pooling in visual recognition, ICML, pp.111-118, 2010. ,
Fast approximate energy minimization via graph cuts, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.23, issue.11, pp.1222-1239, 2001. ,
DOI : 10.1109/34.969114
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.112.6806
Region Merging Techniques Using Information Theory Statistical Measures, IEEE Transactions on Image Processing, vol.19, issue.6, pp.1567-1586, 2010. ,
DOI : 10.1109/TIP.2010.2043008
URL : http://upcommons.upc.edu/bitstream/2117/7488/1/getPDF.pdf
Geodesic active contours, Proceedings of IEEE International Conference on Computer Vision, pp.61-79, 1997. ,
DOI : 10.1109/ICCV.1995.466871
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.21.2196
Semantic image segmentation with task-specific edge detection using CNNs and a discriminatively trained domain transform. arXiv preprint, 2015. ,
Semantic image segmentation with deep convolutional nets and fully connected CRFs, ICLR, 2015. ,
Vehicle Detection in Satellite Images by Hybrid Deep Convolutional Neural Networks, IEEE Geoscience and Remote Sensing Letters, vol.11, issue.10, pp.1797-1801, 2014. ,
DOI : 10.1109/LGRS.2014.2309695
On learning optimized reaction diffusion processes for effective image restoration, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp.5261-5269, 2015. ,
DOI : 10.1109/CVPR.2015.7299163
URL : http://arxiv.org/abs/1503.05768
Deep Learning-Based Classification of Hyperspectral Data, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol.7, issue.6, pp.2094-2107, 2014. ,
DOI : 10.1109/JSTARS.2014.2329330
Spectral–Spatial Classification of Hyperspectral Data Based on Deep Belief Network, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol.8, issue.6, pp.2381-2392, 2015. ,
DOI : 10.1109/JSTARS.2015.2388577
Hyperspectral Remote Sensing Classifications: A Perspective Survey, Transactions in GIS, vol.5, issue.1, 2015. ,
DOI : 10.1109/LGRS.2008.915930
Multi-column deep neural networks for image classification, 2012 IEEE Conference on Computer Vision and Pattern Recognition, pp.3642-3649, 2012. ,
DOI : 10.1109/CVPR.2012.6248110
URL : http://arxiv.org/abs/1202.2745
Fast and accurate deep network learning by exponential linear units (elus). arXiv preprint, 2015. ,
Hyperspectral geological remote sensing: evaluation of analytical techniques, International Journal of Remote Sensing, vol.17, issue.12, pp.2215-2242, 1996. ,
Kernel Density Estimation and Intrinsic Alignment for Shape Priors in Level Set Segmentation, International Journal of Computer Vision, vol.127, issue.2, pp.335-351, 2006. ,
DOI : 10.1007/s11263-006-7533-5
Diffusion snakes: Introducing statistical shape knowledge into the Mumford-Shah functional, International Journal of Computer Vision, vol.50, issue.3, pp.295-313, 2002. ,
DOI : 10.1023/A:1020826424915
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.28.8305
What is a good evaluation measure for semantic segmentation?, Procedings of the British Machine Vision Conference 2013, 2013. ,
DOI : 10.5244/C.27.32
URL : http://www.bmva.org/bmvc/2013/Papers/paper0032/paper0032.pdf
Semiautomatic segmentation with compact shape prior, Image and Vision Computing, vol.27, issue.1-2, pp.206-219, 2009. ,
DOI : 10.1016/j.imavis.2008.02.006
Arnaud Béchet, and Josiane Zerubia Automatic flamingo detection using a multiple birth and death process, IEEE ICASSP, pp.1113-1116, 2008. ,
DOI : 10.1109/icassp.2008.4517809
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.363.9413
Measures of the Amount of Ecologic Association Between Species, Ecology, vol.26, issue.3, pp.297-302, 1945. ,
DOI : 10.2307/1932409
Algorithms for the reduction of the number of points required to represent a digitized line or its caricature, Cartographica, vol.10, issue.2, pp.112-122, 1973. ,
Computational mammography using deep neural networks, Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, vol.15, pp.1-5, 2016. ,
DOI : 10.1007/s11263-015-0816-y
Adaptive subgradient methods for online learning and stochastic optimization, JMLR, vol.12, pp.2121-2159, 2011. ,
Learning Hierarchical Features for Scene Labeling, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.35, issue.8, pp.1915-1929, 2013. ,
DOI : 10.1109/TPAMI.2012.231
URL : https://hal.archives-ouvertes.fr/hal-00742077
Advances in Spectral-Spatial Classification of Hyperspectral Images, Proceedings of the IEEE, vol.101, issue.3 ,
DOI : 10.1109/JPROC.2012.2197589
URL : https://hal.archives-ouvertes.fr/hal-00737075
Representation and detection of deformable shapes, IEEE Trans. Pattern Anal. Mach. Intell, vol.27, issue.2, pp.208-220, 2005. ,
Object detection with discriminatively trained part-based models, IEEE Trans. Pattern Anal. Mach. Intell, vol.32, issue.9, pp.1627-1645, 2010. ,
An Application of Recurrent Neural Networks to Discriminative Keyword Spotting, ICANN, pp.220-229, 2007. ,
DOI : 10.1007/978-3-540-74695-9_23
A coherent interpretation of auc as a measure of aggregated classification performance, ICML, pp.657-664, 2011. ,
Interactive Graph Cut Based Segmentation with Shape Priors, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05), pp.755-762, 2005. ,
DOI : 10.1109/CVPR.2005.191
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.61.1204
Automatic Heart Isolation for CT Coronary Visualization Using Graph-Cuts, 3rd IEEE International Symposium on Biomedical Imaging: Macro to Nano, 2006., pp.614-617, 2006. ,
DOI : 10.1109/ISBI.2006.1624991
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.112.3984
Automated polygon generalization in a multi agent system, 2003. ,
Domain transform for edge-aware image and video processing, ACM Trans. Graph, vol.3069, issue.4, pp.1-6912, 2011. ,
Use of the stair vision library within the ISPRS 2d semantic labeling benchmark (vaihingen), 2015. ,
Learning precise timing with lstm recurrent networks, Journal of machine learning research, vol.3, pp.115-143, 2002. ,
A review on hyperspectral remote sensing for homogeneous and heterogeneous forest biodiversity assessment, International Journal of Remote Sensing, vol.1, issue.7, pp.311837-1856, 2010. ,
DOI : 10.1016/j.rse.2006.06.010
Efficient tree searches with available algorithms, Evolutionary bioinformatics online, vol.3, p.341, 2007. ,
Understanding the difficulty of training deep feedforward neural networks, In AISTATS, pp.249-256, 2010. ,
Deep sparse rectifier neural networks, JMLR, vol.15, issue.106, p.275, 2011. ,
URL : https://hal.archives-ouvertes.fr/hal-00752497
Generative adversarial nets, NIPS, pp.2672-2680, 2014. ,
Fast Trust Region for Segmentation, 2013 IEEE Conference on Computer Vision and Pattern Recognition, pp.1714-1721, 2013. ,
DOI : 10.1109/CVPR.2013.224
Convexity Shape Prior for Segmentation, ECCV, pp.675-690, 2014. ,
DOI : 10.1007/978-3-319-10602-1_44
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.638.9253
Supervised Sequence Labelling, Supervised Sequence Labelling with Recurrent Neural Networks, pp.5-13, 2012. ,
DOI : 10.1007/978-3-642-24797-2_2
True orthophoto production using lidar data, ISPRS Joint Workshop Visualization and Exploration of Geospatial Data, p.4, 2007. ,
Hypercolumns for object segmentation and fine-grained localization, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2015. ,
DOI : 10.1109/CVPR.2015.7298642
URL : http://arxiv.org/abs/1411.5752
Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification, 2015 IEEE International Conference on Computer Vision (ICCV), pp.1026-1034, 2015. ,
DOI : 10.1109/ICCV.2015.123
URL : http://arxiv.org/pdf/1502.01852
Improving neural networks by preventing co-adaptation of feature detectors, 2012. ,
Long Short-Term Memory, Neural Computation, vol.4, issue.8, pp.1735-1780, 1997. ,
DOI : 10.1016/0893-6080(88)90007-X
A graphical model framework for coupling MRFs and deformable models, Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2004. CVPR 2004., pp.739-746, 2004. ,
DOI : 10.1109/CVPR.2004.1315238
The finite element method: linear static and dynamic finite element analysis, 2012. ,
Batch normalization: Accelerating deep network training by reducing internal covariate shift. arXiv preprint, 2015. ,
Caffe, Proceedings of the ACM International Conference on Multimedia, MM '14, 2014. ,
DOI : 10.1145/2647868.2654889
Learning city structures from online maps, 2016. ,
Semantic Segmentation of Small Objects and Modeling of Uncertainty in Urban Remote Sensing Images Using Deep Convolutional Neural Networks, 2016 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), 2016. ,
DOI : 10.1109/CVPRW.2016.90
Recognition-Driven Two-Dimensional Competing Priors Toward Automatic and Accurate Building Detection, IEEE Transactions on Geoscience and Remote Sensing, vol.47, issue.1, pp.133-144, 2009. ,
DOI : 10.1109/TGRS.2008.2002027
A survey of spectral unmixing algorithms. Lincoln Lab, J, vol.14, pp.55-78, 2003. ,
ImageNet classification with deep convolutional neural networks, Communications of the ACM, vol.60, issue.6, 2012. ,
DOI : 10.1162/neco.2009.10-08-881
Obj cut, IEEE CVPR, pp.18-25, 2005. ,
Extraction of complex patterns from multiresolution remote sensing images: A hierarchical top-down methodology, Pattern Recognition, vol.45, issue.2, pp.685-706, 2012. ,
DOI : 10.1016/j.patcog.2011.07.017
Automatic and topology-preserving gradient mesh generation for image vectorization, ACM Trans. on Graphics, vol.28, issue.3, p.85, 2009. ,
DOI : 10.1145/1531326.1531391
URL : http://cg.cs.tsinghua.edu.cn/papers/Siggraph_2009_imagevectorization.pdf
A Scalable Tile-Based Framework for Region-Merging Segmentation, IEEE Transactions on Geoscience and Remote Sensing, vol.53, issue.10 ,
DOI : 10.1109/TGRS.2015.2422848
URL : http://ieeexplore.ieee.org:80/stamp/stamp.jsp?tp=&arnumber=7101250
Ardeco: automatic region detection and conversion, 17th Eurographics Symposium on Rendering, pp.349-360, 2006. ,
URL : https://hal.archives-ouvertes.fr/inria-00105620
Deep learning, Nature, vol.9, issue.7553, pp.436-444, 2015. ,
DOI : 10.1007/s10994-013-5335-x
Gradient-based learning applied to document recognition, Proc. of the IEEE, pp.2278-2324, 1998. ,
DOI : 10.1109/5.726791
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.138.1115
Hyperspectral image classification from multiscale description with constrained connectivity and metric learning, 6th International Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS), 2014. ,
URL : https://hal.archives-ouvertes.fr/hal-00998254
Image Segmentation by Branch-and-Mincut, ECCV, pp.15-29, 2008. ,
DOI : 10.1007/978-3-540-88693-8_2
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.146.2812
Automatic and Precise Orthorectification, Coregistration, and Subpixel Correlation of Satellite Images, Application to Ground Deformation Measurements, IEEE Transactions on Geoscience and Remote Sensing, vol.45, issue.6, pp.1529-1558, 2007. ,
DOI : 10.1109/TGRS.2006.888937
Statistical shape influence in geodesic active contours, IEEE CVPR, pp.316-323, 2000. ,
Random tree optimization for the construction of the most parsimonious phylogenetic trees, 2009 43rd Annual Conference on Information Sciences and Systems, pp.757-762, 2009. ,
DOI : 10.1109/CISS.2009.5054819
Classification of hyperspectral image based on deep belief networks, 2014 IEEE International Conference on Image Processing (ICIP), pp.5132-5136, 2014. ,
DOI : 10.1109/ICIP.2014.7026039
An efficient measure of compactness for two-dimensional shapes and its application in regionalization problems, International Journal of Geographical Information Science, vol.5, issue.27, pp.1227-1250, 2013. ,
DOI : 10.1016/j.ecolmodel.2005.08.022
Learning PDEs for Image Restoration via Optimal Control, ECCV, pp.115-128, 2010. ,
DOI : 10.1007/978-3-642-15549-9_9
Toward designing intelligent PDEs for computer vision: An optimal control approach, Image and Vision Computing, vol.31, issue.1, pp.43-56, 2013. ,
DOI : 10.1016/j.imavis.2012.09.004
URL : http://arxiv.org/pdf/1109.1057
Fully convolutional networks for semantic segmentation, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2015. ,
DOI : 10.1109/CVPR.2015.7298965
URL : http://arxiv.org/pdf/1411.4038
Binary Partition Tree for Semantic Object Extraction and Image Segmentation, IEEE Transactions on Circuits and Systems for Video Technology, vol.17, issue.3, pp.378-383, 2007. ,
DOI : 10.1109/TCSVT.2006.888943
Multiview Deep Learning for Land-Use Classification, IEEE Geoscience and Remote Sensing Letters, vol.12, issue.12, pp.2448-2452, 2015. ,
DOI : 10.1109/LGRS.2015.2483680
Improved partition trees for multi-class segmentation of remote sensing images, 2015 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), pp.1016-1019, 2015. ,
DOI : 10.1109/IGARSS.2015.7325941
URL : https://hal.archives-ouvertes.fr/hal-01182772
Optimizing Partition Trees for Multi-Object Segmentation with Shape Prior, Procedings of the British Machine Vision Conference 2015, 2015. ,
DOI : 10.5244/C.29.64
URL : https://hal.archives-ouvertes.fr/hal-01182776
Fully convolutional neural networks for remote sensing image classification, 2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), pp.5071-5074, 2016. ,
DOI : 10.1109/IGARSS.2016.7730322
URL : https://hal.archives-ouvertes.fr/hal-01350706
Anastasios Doulamis, and Nikolaos Doulamis Deep supervised learning for hyperspectral data classification through convolutional neural networks, IEEE IGARSS, pp.4959-4962, 2015. ,
DOI : 10.1109/igarss.2015.7326945
Semantic segmentation of aerial images with an ensemble of cnns, ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences, pp.473-480, 2016. ,
Enhancing Road Maps by Parsing Aerial Images Around the World, 2015 IEEE International Conference on Computer Vision (ICCV), 2015. ,
DOI : 10.1109/ICCV.2015.197
URL : http://elib.dlr.de/100653/1/roadwidth_for_iccv_final_compressed.pdf
Note on the sampling error of the difference between correlated proportions or percentages, Psychometrika, vol.12, issue.2, pp.153-157, 1947. ,
DOI : 10.1007/BF02295996
Stable Mean-Shift Algorithm and Its Application to the Segmentation of Arbitrarily Large Remote Sensing Images, IEEE Transactions on Geoscience and Remote Sensing, vol.53, issue.2 ,
DOI : 10.1109/TGRS.2014.2330857
Deep Model for Classification of Hyperspectral image using Restricted Boltzmann Machine, Proceedings of the 2014 International Conference on Interdisciplinary Advances in Applied Computing, ICONIAAC '14, p.35, 2014. ,
DOI : 10.1145/2660859.2660946
Cernock`y, and Sanjeev Khudanpur . Recurrent neural network based language model, Interspeech, 2010. ,
Machine learning for aerial image labeling, 2013. ,
Learning to detect roads in highresolution aerial images, ECCV, pp.210-223, 2010. ,
DOI : 10.1007/978-3-642-15567-3_16
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.178.7318
State of the art of compactness and circularity measures, Int. Mathematical Forum, vol.4, issue.27, pp.1305-1335, 2009. ,
Rectified linear units improve restricted boltzmann machines, ICML, pp.807-814, 2010. ,
A Survey and Comparison of Discrete and Continuous Multi-label Optimization Approaches for the Potts Model, International Journal of Computer Vision, vol.3, issue.4, pp.223-240, 2013. ,
DOI : 10.1109/CVPR.2012.6247860
Learning Deconvolution Network for Semantic Segmentation, 2015 IEEE International Conference on Computer Vision (ICCV), pp.1520-1528, 2015. ,
DOI : 10.1109/ICCV.2015.178
URL : http://arxiv.org/pdf/1505.04366
Building Outline Extraction from Digital Elevation Models Using Marked Point Processes, International Journal of Computer Vision, vol.24, issue.5, pp.107-132, 2007. ,
DOI : 10.1142/p060
Van-Den Hengel, et al. Effective semantic pixel labelling with convolutional networks and conditional random fields, IEEE CVPR Workshops, 2015. ,
Occlusion-based depth ordering on monocular images with Binary Partition Tree, 2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp.1093-1096, 2011. ,
DOI : 10.1109/ICASSP.2011.5946598
On the difficulty of training recurrent neural networks, ICML, vol.28, pp.1310-1318, 2013. ,
Enet: A deep neural network architecture for real-time semantic segmentation, 2016. ,
Scale-space and edge detection using anisotropic diffusion, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.12, issue.7, pp.629-639, 1990. ,
DOI : 10.1109/34.56205
URL : http://authors.library.caltech.edu/6498/1/PERieeetpami90.pdf
Object-based vectorization for interactive image editing. The Visual Computer, pp.661-670, 2006. ,
DOI : 10.1007/s00371-006-0051-1
Optimizing curve segmentation in computer graphics, Proceedings of the International Computing Symposium, pp.467-472, 1974. ,
Euler's gem: the polyhedron formula and the birth of topology, 2012. ,
A metric for distributions with applications to image databases, Sixth International Conference on Computer Vision (IEEE Cat. No.98CH36271), pp.59-66, 1998. ,
DOI : 10.1109/ICCV.1998.710701
Topologically Consistent Line Simplification with the Douglas-Peucker Algorithm, Cartography and Geographic Information Science, vol.26, issue.1, pp.7-18, 1999. ,
DOI : 10.1559/152304099782424901
Long short-term memory recurrent neural network architectures for large scale acoustic modeling, Interspeech, pp.338-342, 2014. ,
Low-level processing of PolSAR images with binary partition trees, 2014 IEEE Geoscience and Remote Sensing Symposium, 2014. ,
DOI : 10.1109/IGARSS.2014.6946602
Binary partition tree as an efficient representation for image processing, segmentation, and information retrieval, IEEE Transactions on Image Processing, vol.9, issue.4 ,
DOI : 10.1109/83.841934
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.34.8078
Antiextensive connected operators for image and sequence processing, IEEE Transactions on Image Processing, vol.7, issue.4, pp.555-570, 1998. ,
DOI : 10.1109/83.663500
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.55.9217
Globally Optimal Image Segmentation with an Elastic Shape Prior, 2007 IEEE 11th International Conference on Computer Vision, pp.1-6, 2007. ,
DOI : 10.1109/ICCV.2007.4408972
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.110.8761
Remote sensing: models and methods for image processing, 2006. ,
Convolutional Neural Network Based Automatic Object Detection on Aerial Images, IEEE Geoscience and Remote Sensing Letters, vol.13, issue.5, pp.740-744, 2016. ,
DOI : 10.1109/LGRS.2016.2542358
Fully convolutional networks for dense semantic labelling of highresolution aerial imagery. arXiv preprint, 2016. ,
Performance Evaluation of Line Simplification Algorithms for Vector Generalization, The Cartographic Journal, vol.5, issue.4, pp.27-44, 2006. ,
DOI : 10.1007/3-540-63818-0_5
Density estimation for statistics and data analysis, 1986. ,
Learning to simplify, ACM Transactions on Graphics, vol.35, issue.4, p.121, 2016. ,
DOI : 10.1145/2512349.2512801
Very deep convolutional networks for large-scale image recognition, 2014. ,
Uninitialized, globally optimal, graph-based rectilinear shape segmentation-the opposing metrics method, ICCV, pp.1-8, 2007. ,
Graph cuts segmentation using an elliptical shape prior, IEEE International Conference on Image Processing 2005, pp.1222-1225, 2005. ,
DOI : 10.1109/ICIP.2005.1530282
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.396.7269
Hyperspectral Image Classification with Convolutional Neural Networks, Proceedings of the 23rd ACM international conference on Multimedia, MM '15, pp.1159-1162, 2015. ,
DOI : 10.1109/TGRS.2005.863297
URL : https://biblio.ugent.be/publication/7034491/file/7034499.pdf
Constrained connectivity for hierarchical image partitioning and simplification, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.30, issue.7, pp.1132-1145, 2008. ,
DOI : 10.1109/TPAMI.2007.70817
Striving for simplicity: The all convolutional net, 2014. ,
Dropout: a simple way to prevent neural networks from overfitting, Journal of Machine Learning Research, vol.15, issue.1, pp.1929-1958, 2014. ,
Image vectorization using optimized gradient meshes, ACM Transactions on Graphics, vol.26, issue.3, p.11, 2007. ,
DOI : 10.1145/1276377.1276391
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.306.6165
Graph-cut-based model for spectral-spatial classification of hyperspectral images, 2014 IEEE Geoscience and Remote Sensing Symposium, pp.3418-3421, 2014. ,
DOI : 10.1109/IGARSS.2014.6947216
URL : https://hal.archives-ouvertes.fr/hal-01011495
Improved hierarchical optimization-based classification of hyperspectral images using shape analysis, 2012 IEEE International Geoscience and Remote Sensing Symposium, pp.1409-1412, 2012. ,
DOI : 10.1109/IGARSS.2012.6351272
URL : https://hal.archives-ouvertes.fr/hal-00729038
Incorporating edge information into best merge region-growing segmentation, 2014 IEEE Geoscience and Remote Sensing Symposium, 2014. ,
DOI : 10.1109/IGARSS.2014.6947591
URL : http://hdl.handle.net/2060/20150001295
The rotating calipers: An efficient, multipurpose, computational tool, ICCTIM, pp.215-225, 2014. ,
Mnemonic Descent Method: A Recurrent Process Applied for End-to-End Face Alignment, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp.4177-4187, 2016. ,
DOI : 10.1109/CVPR.2016.453
Hyperspectral Image Representation and Processing With Binary Partition Trees, IEEE Transactions on Image Processing, vol.22, issue.4, pp.1430-1443, 2013. ,
DOI : 10.1109/TIP.2012.2231687
URL : https://hal.archives-ouvertes.fr/hal-00798351
Object recognition in urban hyperspectral images using Binary Partition Tree representation, 2013 IEEE International Geoscience and Remote Sensing Symposium, IGARSS, pp.4098-4101, 2013. ,
DOI : 10.1109/IGARSS.2013.6723734
Star Shape Prior for Graph-Cut Image Segmentation, ECCV, pp.454-467, 2008. ,
DOI : 10.1145/1015706.1015720
Fast stellar mesh simplification, 16th Brazilian Symposium on Computer Graphics and Image Processing (SIBGRAPI 2003), pp.27-34, 2003. ,
DOI : 10.1109/SIBGRA.2003.1240988
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.1.4637
Binary Partition Trees for Object Detection, IEEE Transactions on Image Processing, vol.17, issue.11, pp.2201-2216, 2008. ,
DOI : 10.1109/TIP.2008.2002841
Pointer networks, NIPS, pp.2692-2700, 2015. ,
Line generalisation by repeated elimination of points, The Cartographic Journal, vol.30, issue.1, pp.46-51, 1992. ,
DOI : 10.1179/caj.1993.30.1.46
Dense semantic labeling of sub-decimeter resolution images with convolutional neural networks, IEEE Tran. Geosci. Remote Sens, 2016. ,
Object-based classification of remote sensing data for change detection . ISPRS Journal of photogrammetry and remote sensing, pp.225-238, 2004. ,
Road network extraction: a neural-dynamic framework based on deep learning and a finite state machine, International Journal of Remote Sensing, vol.73, issue.9, pp.3144-3169, 2015. ,
DOI : 10.1109/TIP.2006.887731
Anisotropic diffusion in image processing, Teubner Stuttgart, 1998. ,
Backpropagation through time: what it does and how to do it, Proc. of the IEEE, pp.1550-1560, 1990. ,
DOI : 10.1109/5.58337
The lack of a priori distinctions between learning algorithms, Neural computation, vol.8, issue.7, pp.1341-1390, 1996. ,
A non-self-intersection Douglas-Peucker algorithm, 16th Brazilian Symposium on Computer Graphics and Image Processing (SIBGRAPI 2003), pp.60-66, 2003. ,
DOI : 10.1109/SIBGRA.2003.1240992
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.144.686
Probability estimates for multiclass classification by pairwise coupling, The Journal of Machine Learning Research, vol.5, pp.975-1005, 2004. ,
Patch-based image vectorization with automatic curvilinear feature alignment, ACM Trans. on Graphics, vol.28, issue.5, p.115, 2009. ,
DOI : 10.1145/1618452.1618461
Object Contour Detection with a Fully Convolutional Encoder-Decoder Network, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2016. ,
DOI : 10.1109/CVPR.2016.28
URL : http://arxiv.org/pdf/1603.04530
A survey of shape feature extraction techniques. Pattern recognition, pp.43-90, 2008. ,
URL : https://hal.archives-ouvertes.fr/hal-00446037
Multi-scale context aggregation by dilated convolutions . arXiv preprint, 2015. ,
Spectral???spatial classification of hyperspectral images using deep convolutional neural networks, Remote Sensing Letters, vol.6, issue.6, pp.468-477, 2015. ,
DOI : 10.1109/LGRS.2010.2047711
Visualizing and understanding convolutional networks, 2014. ,
Spectral???Spatial Feature Extraction for Hyperspectral Image Classification: A Dimension Reduction and Deep Learning Approach, IEEE Transactions on Geoscience and Remote Sensing, vol.54, issue.8, pp.4544-4554, 2016. ,
DOI : 10.1109/TGRS.2016.2543748
Conditional Random Fields as Recurrent Neural Networks, 2015 IEEE International Conference on Computer Vision (ICCV), pp.1529-1537, 2015. ,
DOI : 10.1109/ICCV.2015.179
URL : http://arxiv.org/pdf/1502.03240