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Deep Unsupervised Embedding for Remotely Sensed Images Based on Spatially Augmented Momentum Contrast
(IEEE, 2020-07-14)
Convolutional neural networks (CNNs) have achieved great success when characterizing remote sensing (RS) images. However, the lack of sufficient annotated data (together with the high complexity of the RS image domain) ...
Environment-Aware Regression for Indoor Localization based on WiFi Fingerprinting
(Institute of Electrical and Electronics EngineersIEEE, 2021-04-19)
Data enrichment through interpolation or regression is a common approach to deal with sample collection for Indoor Localization with WiFi fingerprinting. This paper provides guidelines on where to collect WiFi samples, and ...
Deep Metric Learning Based on Scalable Neighborhood Components for Remote Sensing Scene Characterization
(Institute of Electrical and Electronics Engineers, 2020-05-12)
With the development of convolutional neural networks (CNNs), the semantic understanding of remote sensing (RS) scenes has been significantly improved based on their prominent feature encoding capabilities. While many ...
Multitemporal Mosaicing for Sentinel-3/FLEX Derived Level-2 Product Composites
(Institute of Electrical and Electronics Engineers, 2020-09-24)
The increasing availability of remote sensing data
raises important challenges in terms of operational data provision
and spatial coverage for conducting global studies and analyses. In
this regard, existing multitemporal ...
Deep Hashing Based on Class-Discriminated Neighborhood Embedding
(Institute of Electrical and Electronics Engineers, 2020-09-30)
Deep-hashing methods have drawn significant attention during the past years in the field of remote sensing (RS)
owing to their prominent capabilities for capturing the semantics
from complex RS scenes and generating the ...
Endmember Extraction From Hyperspectral Imagery Based on Probabilistic Tensor Moments
(Institute of Electrical and Electronics Engineers, 2020-01-13)
This letter presents a novel hyperspectral endmember extraction approach that integrates a tensor-based decomposition scheme with a probabilistic framework in order to take
advantage of both technologies when uncovering ...
Rice-yield prediction with multi-temporal sentinel-2 data and 3D CNN: A case study in Nepal
(Multidisciplinary Digital Publishing Institute, 2021-04-04)
Crop yield estimation is a major issue of crop monitoring which remains particularly
challenging in developing countries due to the problem of timely and adequate data availability.
Whereas traditional agricultural systems ...
Graph Relation Network: Modeling Relations Between Scenes for Multilabel Remote-Sensing Image Classification and Retrieval
(IEEE, 2020-08-21)
Due to the proliferation of large-scale remote-sensing (RS) archives with multiple annotations, multilabel RS scene classification and retrieval are becoming increasingly popular. Although some recent deep learning-based ...
Noise-Tolerant Deep Neighborhood Embedding for Remotely Sensed Images With Label Noise
(IEEE, 2021-02-02)
Recently, many deep learning-based methods have been developed for solving remote sensing (RS) scene classification or retrieval tasks. Most of the adopted loss functions for training these models require accurate annotations. ...
High-Rankness Regularized Semi-Supervised Deep Metric Learning for Remote Sensing Imagery
(MDPI, 2020)
Deep metric learning has recently received special attention in the field of remote sensing (RS) scene characterization, owing to its prominent capabilities for modeling distances among RS images based on their semantic ...