[PDF] Top 20 Low-Shot Learning for the Semantic Segmentation of Remote Sensing Imagery
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Low-Shot Learning for the Semantic Segmentation of Remote Sensing Imagery
... The domain adaptation techniques used in this paper could be greatly improved as the quantity and quality of DIRSIG scenes improves as well. In the future, we could pull data from multiple DIRSIG scenes, increase the ... See full document
137
Semantic Segmentation Based Remote Sensing Data Fusion on Crops Detection
... the remote sensing imagery of different ...Google imagery was applied through the Gram Schmidt pan-sharpen ...GE imagery, as it has showed promising results for all the images have been ... See full document
12
Automatic semantic segmentation and classification of remote sensing data for agriculture
... Ma L., et al. [21] offered object-based image analysis. The availability and accessibility of high resolution RS data create a challenge in RS image classification. To deal with these uncertainties and some limitations, ... See full document
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Remote Sensing / An object-based semantic classification method for high resolution remote sensing imagery using ontology
... object-based semantic classification method for high resolution satellite imagery using an ontology that aims to fully exploit the advantages of ontology to ...machine learning method, and ... See full document
21
LEARNING CLASSIFIERS FOR SCIENCE EVENT DETECTION IN REMOTE SENSING IMAGERY
... Within the test set, the number of pixels belonging to each of the five classes was not evenly distributed. The distribution of pixels over the five classes is shown in Table 3. The overall accuracy of each classifier is ... See full document
8
Road Recognition from Remote Sensing Imagery using Machine Learning
... Gaps which have a high impact on the network topology are closed if evidence supporting this is found in the image. D. Chaudhuri, N. K. Kushwaha, and A. Samal et al. [5] proposed semi-automatic approach for road ... See full document
7
High-Rankness Regularized Semi-Supervised Deep Metric Learning for Remote Sensing Imagery
... Compared with other state-of-the-art methods, our HR-S 2 DML achieves the best performance on the two considered benchmark datasets. As it is posibble to observe, the proposed approach improves the classification ... See full document
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Semantic Segmentation of SLAR Imagery with Convolutional LSTM Selectional AutoEncoders
... However, SLAR has the advantage of being able to control an area with greater precision and at any time (without having to wait for the satellite to be positioned). The basic principle on which the SAR and SLAR sensors ... See full document
22
Machine Learning Based Crop Drought Mapping System by UAV Remote Sensing RGB Imagery
... d School of Automation Science and Electrical Engineering, Beihang University, Beijing 100191, China Water stress has adverse effects on crop growth and yield, where its monitoring plays a vital role in precision crop ... See full document
12
Object-based Morphological Profiles for Classification of Remote Sensing Imagery
... and segmentation scales of the same morphological operations), which can be critical for the estimation of statistics in parametric approaches ...ensemble learning method for classification and ... See full document
23
SEGMENTATION OF HIGHER SPATIAL RESOLUTION REMOTE SENSING DATA
... of segmentation parameters using fuzzy approach gives an automated value for the ...Image segmentation plays a key role in object extraction in higher spatial resolution ...extensive semantic ... See full document
7
Image Segmentation Techniques with Remote Sensing Perspective A Review
... detection segmentation algorithm refers to the use of different boundaries of the image Pixel gray or color discontinuity detection area of the edge in order to achieve image separation ...the segmentation ... See full document
6
Learning a multi-branch neural network from multiple sources for knowledge adaptation in remote sensing imagery
... of remote sensing, in the literature there are few works related to single source domain adaptation approaches based on deep learning techniques and mainly related to cross-scene ...the low ... See full document
18
Deep learning for urban remote sensing
... A. Deep network architecture We use the SegNet architecture from [3]. SegNet uses an encoder-decoder architecture (cf. Fig. 3). The encoder is based on VGG-16 [6], in which convolutions are followed by a batch ... See full document
5
Regularization destriping of remote sensing imagery
... Abstract. We illustrate the utility of variational destriping for ocean color images from both multispectral and hyper- spectral sensors. In particular, we examine data from a filter spectrometer, the Visible Infrared ... See full document
12
Automated detection of snow avalanche deposits: segmentation and classification of optical remote sensing imagery
... The Davos-Parsenn Ski Resort, located near the town of Davos is subject to a high annual frequency of avalanches; a large number of them are artificially triggered to secure the ski slopes. Due to the difficulties in ... See full document
14
Few-shot 3D Point Cloud Semantic Segmentation
... voxel grids and multi-view images. Despite its simplicity and efficiency, PointNet overlooks the important local infor- mation embedded in the neighboring points. DGCNN [24] addresses this issue by designing the EdgeConv ... See full document
10
Monitoring agricultural plantations with remote sensing imagery
... plantations remote sensing spectral bands, vegetation INTRODUCTION Remote sensing refers to the registration activities, observation and perception of distant objects or ...In remote ... See full document
7
Semantic Segmentation of Aerial Imagery using U-Nets
... in semantic segmen- ...combines semantic informa- tion from a deep, coarse layer with appearance information from a shallow, fine layer to produce accurate and detailed ...state-of-the-art ... See full document
99
Landslide detection using satellite remote sensing imagery
... 2 Department of Natural Resources, Chinese Culture University, 55, Hwa Kang Rd, Yangmingshan, Taipei, Taiwan 3 Department of Geography, Chinese Culture University, 55, Hwa Kang Rd, Yangmingshan, Taipei, Taiwan ARTICLE ... See full document
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