Do deep features generalize from everyday objects to remote sensing and aerial scenes domains?
OAB Penatti, K Nogueira… - Proceedings of the IEEE …, 2015 - cv-foundation.org
In this paper, we evaluate the generalization power of deep features (ConvNets) in two new
scenarios: aerial and remote sensing image classification. We evaluate experimentally …
scenarios: aerial and remote sensing image classification. We evaluate experimentally …
A secure mobile crowdsensing game with deep reinforcement learning
Mobile crowdsensing (MCS) is vulnerable to faked sensing attacks, as selfish smartphone
users sometimes provide faked sensing results to the MCS server to save their sensing costs …
users sometimes provide faked sensing results to the MCS server to save their sensing costs …
Improving spatial feature representation from aerial scenes by using convolutional networks
K Nogueira, WO Miranda… - 2015 28th SIBGRAPI …, 2015 - ieeexplore.ieee.org
The performance of image classification is highly dependent on the quality of extracted
features. Concerning high resolution remote image images, encoding the spatial features in …
features. Concerning high resolution remote image images, encoding the spatial features in …
A framework for selection and fusion of pattern classifiers in multimedia recognition
The frequent growth of visual data, either by countless monitoring video cameras wherever
we go or the popularization of mobile devices that allow each person to create and edit their …
we go or the popularization of mobile devices that allow each person to create and edit their …
[HTML][HTML] Applying machine learning based on multiscale classifiers to detect remote phenology patterns in Cerrado savanna trees
Plant phenology is one of the most reliable indicators of species responses to global climate
change, motivating the development of new technologies for phenological monitoring …
change, motivating the development of new technologies for phenological monitoring …
Efficient and effective hierarchical feature propagation
JA dos Santos, OAB Penatti… - IEEE Journal of …, 2014 - ieeexplore.ieee.org
Many methods have been recently proposed to deal with the large amount of data provided
by the new remote sensing technologies. Several of those methods rely on the use of …
by the new remote sensing technologies. Several of those methods rely on the use of …
Coffee crop recognition using multi-scale convolutional neural networks
Identifying crops from remote sensing images is a fundamental to know and monitor land-
use. However, manual identification is expensive and maybe impracticable given the …
use. However, manual identification is expensive and maybe impracticable given the …
Rank aggregation for pattern classifier selection in remote sensing images
FA Faria, DCG Pedronette… - IEEE Journal of …, 2014 - ieeexplore.ieee.org
In the past few years, segmentation and classification techniques have become a
cornerstone of many successful remote sensing algorithms aiming at delineating geographic …
cornerstone of many successful remote sensing algorithms aiming at delineating geographic …
Pointwise and pairwise clothing annotation: combining features from social media
In this paper, we present effective algorithms to automatically annotate clothes from social
media data, such as Facebook and Instagram. Clothing annotation can be informally stated …
media data, such as Facebook and Instagram. Clothing annotation can be informally stated …
Classifier selection based on the correlation of diversity measures: When fewer is more
The ever-growing access to high-resolution images has prompted the development of
region-based classification methods for remote sensing images. However, in agricultural …
region-based classification methods for remote sensing images. However, in agricultural …