SAR ship detection using sea-land segmentation-based convolutional 393 neural network, detection. International Workshop on Remote Sensing with Intelligent Processing, vol.396, p.16, 2017. ,
Automatic ship detection in Single-Pol SAR Images using 397 texture features in artificial neural networks. The International Archives of Photogrammetry, Remote Sensing 398 and Spatial Information Sciences, vol.40, p.17, 2015. ,
Very deep learning for ship 400 discrimination in synthetic aperture radar imagery, IEEE International Geoscience and Remote Sensing 401 Symposium (IGARSS), pp.104-107, 2016. ,
Size and Heading of SAR-Detected Ships through the Inertia Tensor ,
, Multidisciplinary Digital Publishing Institute Proceedings, vol.2, p.19, 2018.
The exploitation of Sentinel-1 images for vessel size estimation, Remote Sensing 405 Letters, vol.7, pp.1219-1228, 2016. ,
Fully convolutional networks for semantic segmentation, IEEE 407 Conference on Computer Vision and Pattern Recognition, vol.408, p.21, 2015. ,
Imagenet classification with deep convolutional neural networks ,
, Advances in neural information processing systems, pp.1097-1105, 2012.
Very deep convolutional networks for large-scale image recognition, 2014. ,
Self-normalizing neural networks, Advances in, p.413 ,
, Neural Information Processing Systems, vol.414, p.24, 2017.
The importance of skip connections in 415 biomedical image segmentation, Deep Learning and Data Labeling ,
Deep learning classification of land cover and crop 418 types using remote sensing data. IEEE Geoscience and Remote Sensing Letters, vol.14, p.26, 2017. ,
High-resolution SAR image classification via deep 420 convolutional autoencoders, IEEE Geoscience and Remote Sensing Letters, vol.12, p.27, 2015. ,
Deep residual learning for image recognition, p.422 ,
Lecture 6.5-rmsprop: Divide the gradient by a running average of its recent 424 magnitude, vol.425, p.29, 2012. ,
, A dataset, p.426
, Sentinel-1 ship interpretation, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol.427, issue.2017, p.30
Detecting mammals in UAV images: Best practices to address a 429 substantially imbalanced dataset with deep learning. Remote Sensing of Environment, Chollet, F.; others. Keras, vol.216, p.32, 2015. ,
Multi-layer perceptrons, 432 Computational Intelligence ,
Rich feature hierarchies for accurate object detection and 434 semantic segmentation, Proceedings of the IEEE conference on computer vision and pattern recognition, vol.436, p.34, 2014. ,
The distribution of the flora in the alpine zone, New phytologist, vol.1, p.35, 1912. ,
A coefficient of agreement for nominal scales, vol.438, pp.37-46, 1960. ,
Satellite image-based ship classification method with sentinel-1 ,
, IW mode data, IEEE International Geoscience and Remote Sensing Symposium (IGARSS), pp.441-1300, 2019.
Iceberg detection capabilities of RADARSAT synthetic 443 aperture radar, Canadian Journal of Remote Sensing, vol.27, p.38, 2001. ,
, Ship-iceberg discrimination with convolutional neural networks