Search results for "RECOGNITION"
showing 10 items of 3607 documents
PIECEWISE ANOMALY DETECTION USING MINIMAL LEARNING MACHINE FOR HYPERSPECTRAL IMAGES
2021
Abstract. Hyperspectral imaging, with its applications, offers promising tools for remote sensing and Earth observation. Recent development has increased the quality of the sensors. At the same time, the prices of the sensors are lowering. Anomaly detection is one of the popular remote sensing applications, which benefits from real-time solutions. A real-time solution has its limitations, for example, due to a large amount of hyperspectral data, platform’s (drones or a cube satellite) constraints on payload and processing capability. Other examples are the limitations of available energy and the complexity of the machine learning models. When anomalies are detected in real-time from the hyp…
Robustness of PET Radiomics Features: Impact of Co-Registration with MRI
2021
Radiomics holds great promise in the field of cancer management. However, the clinical application of radiomics has been hampered by uncertainty about the robustness of the features extracted from the images. Previous studies have reported that radiomics features are sensitive to changes in voxel size resampling and interpolation, image perturbation, or slice thickness. This study aims to observe the variability of positron emission tomography (PET) radiomics features under the impact of co-registration with magnetic resonance imaging (MRI) using the difference percentage coefficient, and the Spearman’s correlation coefficient for three groups of images: (i) original PET, (ii) PET after co-…
Learning non-linear time-scales with kernel -filters
2009
A family of kernel methods, based on the @c-filter structure, is presented for non-linear system identification and time series prediction. The kernel trick allows us to develop the natural non-linear extension of the (linear) support vector machine (SVM) @c-filter [G. Camps-Valls, M. Martinez-Ramon, J.L. Rojo-Alvarez, E. Soria-Olivas, Robust @c-filter using support vector machines, Neurocomput. J. 62(12) (2004) 493-499.], but this approach yields a rigid system model without non-linear cross relation between time-scales. Several functional analysis properties allow us to develop a full, principled family of kernel @c-filters. The improved performance in several application examples suggest…
Robust γ-filter using support vector machines
2009
This Letter presents a new approach to time-series modelling using the support vector machines (SVM). Although the g-filter can provide stability in several time-series models, the SVM is proposed here to provide robustness in the estimation of the g-filter coefficients. Examples in chaotic time-series prediction and channel equalization show the advantages of the joint SVM g-filter. Teoría de la Señal y Comunicaciones
A Simple Fusion Method for Image Time Series Based on the Estimation of Image Temporal Validity
2015
High-spatial-resolution satellites usually have the constraint of a low temporal frequency, which leads to long periods without information in cloudy areas. Furthermore, low-spatial-resolution satellites have higher revisit cycles. Combining information from high- and low- spatial-resolution satellites is thought a key factor for studies that require dense time series of high-resolution images, e.g., crop monitoring. There are several fusion methods in the bibliography, but they are time-consuming and complicated to implement. Moreover, the local evaluation of the fused images is rarely analyzed. In this paper, we present a simple and fast fusion method based on a weighted average of two in…
Análisis de métodos de validación cruzada para la obtención robusta de parámetros biofísicos
2015
[EN] Non-parametric regression methods are powerful statistical methods to retrieve biophysical parameters from remote sensing measurements. However, their performance can be affected by what has been presented during the training phase. To ensure robust retrievals, various cross-validation sub-sampling methods are often used, which allow to evaluate the model with subsets of the field dataset. Here, two types of cross-validation techniques were analyzed in the development of non-parametric regression models: hold-out and k-fold. Selected non-parametric linear regression methods were least squares Linear Regression (LR) and Partial Least Squares Regression (PLSR), and nonlinear methods were…
Metodo di Template Matching per l'Analisi di Immagini
2012
La presente invenzione si riferisce ad un metodo di Template Matching per l’analisi di immagini da ImmunoFluorescenza Indiretta (IFI) per la rivelazione e classificazione automatica di pattern autoanticorpali. L’invenzione qui presentata generalizza il metodo del Template Matching operando innovativamente il mapping del contenuto visuale dell’immagine con particolari funzioni discrete qui denominate “mappatori”; inoltre, utilizzando le informazioni provenienti dalla sovrapposizione dei vari mappatori con un metodo di confronto funzionale, realizza una funzione di correlazione originale. La metodologia descritta nel seguito presenta una flessibilità tale da renderla applicabile a qualsiasi p…
Segmentation d'images robuste appliqué à l'imagerie par résonance magnétique et l'échographie de la prostate
2012
Prostate segmentation in trans rectal ultrasound (TRUS) and magnetic resonanceimages (MRI) facilitates volume estimation, multi-modal image registration, surgicalplaning and image guided prostate biopsies. The objective of this thesis is to developshape and region prior deformable models for accurate, robust and computationallyefficient prostate segmentation in TRUS and MRI images. Primary contributionof this thesis is in adopting a probabilistic learning approach to achieve soft classificationof the prostate for automatic initialization and evolution of a shape andregion prior deformable models for prostate segmentation in TRUS images. Twodeformable models are developed for the purpose. An…
Aromatic Bridged Bis-phenol A Derived Cyclophanes. Synthesis, Molecular Structure and Binding Properties Toward Quats
2003
Three novel polyoxyethylene bridged bis phenol A derived cyclophanes, {\rm 2 -- 4,} with additional aromatic units in the bridge to increase the number of cation–π interactions with guest cations, were synthesized and characterized by means of X-ray crystal structure determinations. The binding properties of these receptors toward tetramethylammonium (TMA), N-methylpyridinium (NMP), acetylcholine (ACh) and N-methylquinolinium (NMQ) salts were evaluated by means of 1H NMR spectroscopy and compared with those of the previously reported receptor 1.
Polyether-bridged cyclophanes incorporating bisphenol A units as neutral receptors for quats: synthesis, molecular structure and binding properties
2001
Two novel neutral polyoxyethylene bridged cyclophanes (2a and 2b) incorporating bisphenol A units were synthesized and characterized by means of x-ray crystal structure determination. The binding properties of 2a and 2b toward tetramethylammonium, N-methylpyridinium, and acetylcholine cations were evaluated by means of 1H NMR spectroscopy. Consistent with indications provided by the molecular structure, the cavity in the basket-like cyclophanes is large enough to accommodate the given guest cations conveniently. Circumstantial evidence was obtained that 1,1,2,2-tetrachloroethane is too large to enter the cavity of the smaller cyclophane 2a, but can be included in the cavity of the larger cy…