AIMC Topic: Remote Sensing Technology

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Leveraging variable sensor spatial acuity with a homogeneous, multi-scale place recognition framework.

Biological cybernetics
Most robot navigation systems perform place recognition using a single-sensor modality and one, or at most two heterogeneous map scales. In contrast, mammals perform navigation by combining sensing from a wide variety of modalities including vision, ...

A Two-Stream Deep Fusion Framework for High-Resolution Aerial Scene Classification.

Computational intelligence and neuroscience
One of the challenging problems in understanding high-resolution remote sensing images is aerial scene classification. A well-designed feature representation method and classifier can improve classification accuracy. In this paper, we construct a new...

Fuzziness-based active learning framework to enhance hyperspectral image classification performance for discriminative and generative classifiers.

PloS one
Hyperspectral image classification with a limited number of training samples without loss of accuracy is desirable, as collecting such data is often expensive and time-consuming. However, classifiers trained with limited samples usually end up with a...

From ships to robots: The social relations of sensing the world ocean.

Social studies of science
The dominant practices of physical oceanography have recently shifted from being based on ship-based ocean sampling and sensing to being based on remote and robotic sensing using satellites, drifting floats and remotely operated and autonomous underw...

Underwater Inherent Optical Properties Estimation Using a Depth Aided Deep Neural Network.

Computational intelligence and neuroscience
Underwater inherent optical properties (IOPs) are the fundamental clues to many research fields such as marine optics, marine biology, and underwater vision. Currently, beam transmissometers and optical sensors are considered as the ideal IOPs measur...

A patch-based convolutional neural network for remote sensing image classification.

Neural networks : the official journal of the International Neural Network Society
Availability of accurate land cover information over large areas is essential to the global environment sustainability; digital classification using medium-resolution remote sensing data would provide an effective method to generate the required land...

Matrix and Tensor Completion on a Human Activity Recognition Framework.

IEEE journal of biomedical and health informatics
Sensor-based activity recognition is encountered in innumerable applications of the arena of pervasive healthcare and plays a crucial role in biomedical research. Nonetheless, the frequent situation of unobserved measurements impairs the ability of m...

A machine learning approach to estimation of downward solar radiation from satellite-derived data products: An application over a semi-arid ecosystem in the U.S.

PloS one
Shortwave solar radiation is an important component of the surface energy balance and provides the principal source of energy for terrestrial ecosystems. This paper presents a machine learning approach in the form of a random forest (RF) model for es...

Fuzzy Classification of High Resolution Remote Sensing Scenes Using Visual Attention Features.

Computational intelligence and neuroscience
In recent years the spatial resolutions of remote sensing images have been improved greatly. However, a higher spatial resolution image does not always lead to a better result of automatic scene classification. Visual attention is an important charac...

Remote sensing-based measurement of Living Environment Deprivation: Improving classical approaches with machine learning.

PloS one
This paper provides evidence on the usefulness of very high spatial resolution (VHR) imagery in gathering socioeconomic information in urban settlements. We use land cover, spectral, structure and texture features extracted from a Google Earth image ...