Search results for "estimation"

A Proposal to estimate the roaming–dog Total in an urban area through a PPSWOR spatial sampling with sample size greater than two

2018

Physics-aware Gaussian processes in remote sensing

2018

Abstract Earth observation from satellite sensory data poses challenging problems, where machine learning is currently a key player. In recent years, Gaussian Process (GP) regression has excelled in biophysical parameter estimation tasks from airborne and satellite observations. GP regression is based on solid Bayesian statistics, and generally yields efficient and accurate parameter estimates. However, GPs are typically used for inverse modeling based on concurrent observations and in situ measurements only. Very often a forward model encoding the well-understood physical relations between the state vector and the radiance observations is available though and could be useful to improve pre…

Rapid parameter estimation of discrete decaying signals using autoencoder networks

2021

Machine learning: science and technology 2(4), 045024 (2021). doi:10.1088/2632-2153/ac1eea

Synergistic integration of optical and microwave satellite data for crop yield estimation

2019

Developing accurate models of crop stress, phenology and productivity is of paramount importance, given the increasing need of food. Earth observation (EO) remote sensing data provides a unique source of information to monitor crops in a temporally resolved and spatially explicit way. In this study, we propose the combination of multisensor (optical and microwave) remote sensing data for crop yield estimation and forecasting using two novel approaches. We first propose the lag between Enhanced Vegetation Index (EVI) derived from MODIS and Vegetation Optical Depth (VOD) derived from SMAP as a new joint metric combining the information from the two satellite sensors in a unique feature or des…

Aerial Spectrum Surveying: Radio Map Estimation with Autonomous UAVs

2020

Radio maps are emerging as a popular means to endow next-generation wireless communications with situational awareness. In particular, radio maps are expected to play a central role in unmanned aerial vehicle (UAV) communications since they can be used to determine interference or channel gain at a spatial location where a UAV has not been before. Existing methods for radio map estimation utilize measurements collected by sensors whose locations cannot be controlled. In contrast, this paper proposes a scheme in which a UAV collects measurements along a trajectory. This trajectory is designed to obtain accurate estimates of the target radio map in a short time operation. The route planning a…

Adaptive motion estimation and video vector quantization based on spatiotemporal non-linearities of human perception

1997

The two main tasks of a video coding system are motion estimation and vector quantization of the signal. In this work a new splitting criterion to control the adaptive decomposition for the non-uniform optical flow estimation is exposed. Also, a novel bit allocation procedure is proposed for the quantization of the DCT transform of the video signal. These new approaches are founded on a perception model that reproduce the relative importance given by the human visual system to any location in the spatial frequency, temporal frequency and amplitude domain of the DCT transform. The experiments show that the proposed procedures behave better than their equivalent (fixed-block-size motion estim…

Incipient damage identification through characteristics of the analytical signal response

2008

The analytical signal is a complex representation of a time domain signal: the real part is the time domain signal itself, while the imaginary part is its Hilbert transform. It has been observed that damage, even at a very low level, yields clearly detectable variations of analytical signal quantities such as phase and instantaneous frequency. This observation can represent a step toward a quick and effective tool to recognize the presence of incipient damage where other frequency-based techniques fail. In this paper a damage identification procedure based on an adimensional functional of the square of the difference between the characteristics of the analytical theoretical and measured sig…

Flip angle considerations in (3)helium-MRI.

2000

3Helium-MRI ((3)He-MRI) can be used for analysis of lung function, e. g. dynamic imaging of ventilation and gas diffusion within the lung, assessment of intrapulmonary oxygen concentrations and their time course. During imaging, the irreversible signal loss due to depolarizing radio frequency excitations can be described using the flip angle (FA) alpha. This parameter has to be quantified in order to account for it during quantitative assessment of the (3)helium signal intensity and its temporal development. This technical report reviews two different methods to determine alpha. Limitations and possible error sources of each method are discussed.

Rounding noise effects’ reduction for estimated movement of speckle patterns

2018

The problem of resolution enhancement for speckle patterns analysis-based movement estimation is considered. In our previous publications we showed that this movement represents the corresponding tilt vibrations of the illuminated object and can be measured as a relative spatial shift between time adjacent images of the speckle pattern. In this paper we show how to overcome the resolution limitation obtained when using an optical sensor available in an optical mouse and which measures the Cartesian coordinates of the shift as an integer number of pixels. To overcome such a resolution limitation, it is proposed here to use simultaneous measurements from the same illuminated spot by a few cam…

Support Vector Machines Framework for Linear Signal Processing

2005

This paper presents a support vector machines (SVM) framework to deal with linear signal processing (LSP) problems. The approach relies on three basic steps for model building: (1) identifying the suitable base of the Hilbert signal space in the model, (2) using a robust cost function, and (3) minimizing a constrained, regularized functional by means of the method of Lagrange multipliers. Recently, autoregressive moving average (ARMA) system identification and non-parametric spectral analysis have been formulated under this framework. The generalized, yet simple, formulation of SVM LSP problems is particularized here for three different issues: parametric spectral estimation, stability of I…