, The single channel equivalent was trained with the same data but only for elevation set one. The tuples were of the form <slr_dem, lr_dem>, where slr_dem: the super-low resolution elevation data and lr_dem: the GT low-resolution elevation data
Fully Connected Layers in Convolutional Neural Networks: The Complete Guide, vol.9, 2019. ,
Simultaneous extraction of roads and buildings in remote sensing imagery with convolutional neural networks, ISPRS Journal of Photogrammetry and Remote Sensing, vol.130, pp.139-149, 2017. ,
URL : https://hal.archives-ouvertes.fr/hal-01672877
Chasing Uptake: Super-Resolution Microscopy in Endocytosis and Phagocytosis, Trends in cell biology, 2019. ,
Evaluating super-resolution reconstruction of satellite images, Acta Astronautica, vol.153, pp.15-25, 2018. ,
Deep sparse rectifier neural networks, Proceedings of the fourteenth international conference on artificial intelligence and statistics, pp.315-323, 2011. ,
URL : https://hal.archives-ouvertes.fr/hal-00752497
A learning algorithm for multilayered neural networks based on linear least squares problems, Neural Networks, vol.6, issue.1, pp.127-131, 1993. ,
Super-resolution from image sequences-a review, pp.374-378, 1998. ,
Machine learning mastery, vol.9, 2019. ,
A gradient method for optimizing multi-stage allocation processes, Proc. Harvard Univ. Symposium on digital computers and their applications, vol.72, 1961. ,
A steepest-ascent method for solving optimum programming problems, Journal of Applied Mechanics, vol.29, issue.2, pp.247-257, 1962. ,
A computational approach to edge detection, IEEE Transactions, issue.6, pp.679-698, 1986. ,
Pseudo-grid based building extraction using airborne LIDAR data, Int. Arch. Photogramm. Remote Sens, vol.35, pp.378-381, 2004. ,
Mean shift: a robust approach toward feature space analysis, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.24, issue.5, pp.603-619, 2002. ,
Example-based single document image super-resolution: a global MAP approach with outlier rejection. Multidimensional Systems and Signal Processing, vol.18, pp.103-121, 2007. ,
The helmholtz machine, Neural computation, vol.7, issue.5, pp.889-904, 1995. ,
Image Super-Resolution Using Deep Convolutional Networks, Retrieved from Image Super-Resolution Using Deep Convolutional Networks, 2019. ,
Image super-resolution using deep convolutional networks, IEEE transactions on pattern analysis and machine intelligence, vol.38, pp.295-307, 2015. ,
An empirical study of learning speed in back-propagation networks, 1991. ,
09 03). A History of Deep Learning. Retrieved from import, 2019. ,
Processing of Ikonos imagery for submetre 3D positioning and building extraction, Journal of Photogrammetry and Remote Sensing, vol.56, issue.3, pp.177-194, 2002. ,
Neocognitron: A self-organizing neural network model for a mechanism of pattern recognition unaffected by shift in position, In Biological cybernetics, vol.36, issue.4, pp.193-202, 1980. ,
Extraction of buildings and trees in urban environments, Isprs journal of photogrammetry and remote sensing, vol.54, pp.130-137, 1999. ,
A fast learning algorithm for deep belief nets, Neural computation, vol.18, issue.7, pp.1527-1554, 2006. ,
Three-dimensional super-resolution imaging by stochastic optical reconstruction microscopy, Science, issue.5864, pp.810-813, 2008. ,
Super-resolution method for face recognition using nonlinear mappings on coherent features, IEEE Transactions on Neural Networks, vol.22, issue.1, pp.121-130, 2010. ,
Neural network design and the complexity of learning, 1990. ,
Gradient theory of optimal flight paths, Ars Journal, vol.30, issue.10, pp.947-954, 1960. ,
A survey of the recent architectures of deep convolutional neural networks, 2019. ,
Development of a graph-based approach for building detection, Image and Vision Computing, vol.17, issue.1, pp.3-14, 1999. ,
Imagenet classification with deep convolutional neural networks, Advances in neural information processing systems, pp.1097-1105, 2012. ,
Imagenet classification with deep convolutional neural networks, Advances in neural information processing systems, pp.1097-1105, 2012. ,
Kolmogorov's theorem and multilayer neural networks, Neural networks, vol.5, issue.3, pp.501-506, 1992. ,
Automatic building extraction from DEMs using an object approach and application to the 3D-city modeling, ISPRS Journal of photogrammetry and remote sensing, vol.63, pp.365-381, 2008. ,
URL : https://hal.archives-ouvertes.fr/hal-00781689
3D-city modeling with a digital one-eye stereo system, Proceedings of the XVIII ISPRS-Congress, 1996. ,
A time-delay neural network architecture for isolated word recognition, Neural networks, vol.3, issue.1, pp.23-43, 1990. ,
A tutorial on deep learning part 2: Autoencoders, convolutional neural networks and recurrent neural networks, Google Brain, pp.1-20, 2015. ,
Une procedure d'apprentissage ponr reseau a seuil asymetrique, Proceedings of Cognitiva, vol.85, pp.599-604, 1985. ,
Deep learning, Nature, vol.521, issue.7553, p.436, 2015. ,
Deep into the brain: artificial intelligence in stroke imaging, Journal of stroke, vol.19, issue.3, p.277, 2017. ,
Accurate and robust face recognition from RGB-D images with a deep learning approach, p.123, 2016. ,
The representation of the cumulative rounding error of an algorithm as a Taylor expansion of the local rounding errors, Helsinski: Univ. Helsinki, pp.6-7, 1970. ,
Theory of edge detection, Proc. Roy.Soc. London B, vol.207, pp.187-217, 1980. ,
Automatic extraction of man-made objects from aerial and space images, pp.97-108, 1997. ,
Two algorithms for extracting building models from raw laser altimetry data. ISPRS Journal of photogrammetry and remote sensing, vol.54, pp.153-163, 1999. ,
MatConvNet: CNNs for MATLAB ,
, Parallel distributed processing, vol.1, 1987.
Novel algorithms for 3D surface point cloud boundary detection and edge reconstruction, Journal of Computational Design and Engineering, vol.6, issue.1, pp.81-91, 2019. ,
Perceptrons: An introduction to computational geometry, 2017. ,
A focused backpropagation algorithm for temporal. Backpropagation: Theory, architectures, and applications, p.137, 1995. ,
09 05). A Beginner's Guide to Neural Networks and Deep Learning, 2019. ,
How the backpropagation algorithm works, 2019. ,
Automated detection of arbitrarily shaped buildings in complex environments from monocular VHR optical satellite imagery, Neural computation, vol.12, issue.10, pp.2385-2404, 2012. ,
Building outline extraction from digital elevation models using marked point processes, In International Journal of Computer Vision, vol.72, issue.2, pp.107-132, 2007. ,
Determination of over-learning and overfitting problem in back propagation neural network, International Journal on Soft Computing, vol.2, issue.2, pp.40-51, 2011. ,
Building Detection and Reconstruction fromMid-and High-Resolution Aerial Imagery, COMPUTER VISION AND IMAGE UNDERSTANDING, pp.122-142, 1998. ,
The role of context and model in urban aerial image interpretation focusing on buildings, IEEE International Conference on Networking, Sensing and Control, vol.1, pp.1-12, 2004. ,
Extracting and labeling boundary segments in natural scenes, IEEE Transactions on Pattern Analysis and Machine Intelligence, pp.16-27, 1980. ,
Extracting and labeling boundary segments in natural scenes, IEEE Transactions on Pattern Analysis and Machine Intelligence, issue.1, pp.16-27, 1980. ,
Searching for activation functions, 2017. ,
Segmentation based building detection approach from LiDAR point cloud, The Egyptian Journal of Remote Sensing and Space Science, vol.20, issue.1, pp.71-77, 2017. ,
Rprop-description and implementation details, 1994. ,
, A. g. images, 2003.
URL : https://hal.archives-ouvertes.fr/hal-00535124
A new method for building extraction in urban areas from highresolution LIDAR data, International Archives of Photogrammetry Remote Sensing and Spatial Information Sciences, vol.34, p.295, 2002. ,
Learning internal representations by error propagation (No. ICS-8506), 1985. ,
Learning internal representations by error propagation (No. ICS-8506), 1985. ,
The neural heat exchanger, 1996. ,
Deep learning in neural networks, 2015. ,
Conditioning of quasi-Newton methods for function minimization, Mathematics of computation, vol.24, issue.111, pp.647-656, 1970. ,
Activation Functions in Neural Networks, 2019. ,
, COMBINING EXPLANATION-BASED AND NEURAL LEARNING: AN ALGORITHM AND EMPmiCAL RESULTS, 1989.
, Very deep convolutional networks for large-scale image recognition, pp.1409-1556, 2014.
Data fusion of high-resolution satellite imagery and LiDAR data for automatic building extraction, ISPRS Journal of Photogrammetry and Remote Sensing, vol.62, pp.43-63, 2007. ,
Image processing, analysis, and machine vision, Cengage Learning, 2014. ,
Compiling fast partial derivatives of functions given by algorithms, 1980. ,
, UIUCDCS-R-80-1002)
, Numerische Mathematik, vol.5, 1989.
Deep learning approach for network intrusion detection in software defined networking, International Conference on Wireless Networks and Mobile Communications, 2016. ,
Building detection in very high resolution multispectral data with deep learning features, IEEE International Geoscience and Remote Sensing Symposium (IGARSS), p.1873, 2015. ,
URL : https://hal.archives-ouvertes.fr/hal-01264084
Intelligent pattern recognition techniques for the development of multimodal representation of urban areas, 2013. ,
Mean shift-based preprocessing methodology for improved 3D buildings reconstruction, WASET Int. J. Civ. Environ. Struct. Constr. Architectural Eng, vol.9, issue.5, pp.575-580, 2015. ,
URL : https://hal.archives-ouvertes.fr/hal-01295400
Intelligent pattern recognition techniques for the development of multimodal representation of urban areas, 2013. ,
Estimation of high resolution images and registration parameters from low resolution observations. Iberoamerican Congress on Pattern Recognition, 2004. ,
Enhancing resolution of digital rock images with Super Resolution Convolutional Neural Networks, Journal of Petroleum Science and Engineering, p.106261, 2019. ,
Applications of advances in nonlinear sensitivity analysis. System modeling and optimization, pp.762-770, 1982. ,
Adaptive back-propagation in on-line learning of multilayer networks, Advances in Neural Information Processing Systems, pp.323-329, 1996. ,
Image super-resolution via sparse representation, IEEE transactions on image processing, vol.19, issue.11, pp.2861-2873, 2010. ,
Learning building extraction in aerial scenes with convolutional networks, IEEE transactions on pattern analysis and machine intelligence, vol.40, pp.2793-2798, 2017. ,