Search results for "Pattern"
showing 10 items of 4203 documents
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…
Review of Non-English Corpora Annotated for Emotion Classification in Text
2020
In this paper we try to systematize the information about the available corpora for emotion classification in text for languages other than English with the goal to find what approaches could be used for low-resource languages with close to no existing works in the field. We analyze the corresponding volume, emotion classification schema, language of each corresponding corpus and methods employed for data preparation and annotation automation. We’ve systematized twenty-four papers representing the corpora and found that corpora were mostly for the most spoken world languages: Hindi, Chinese, Turkish, Arabic, Japanese etc. A typical corpus contained several thousand of manually-annotated ent…
Development of an Automatic Pollen Classification System Using Shape, Texture and Aperture Features
2015
International audience; Automatic detection and classification of pollen species has value for use inside of palynologic allergen studies. Traditional labeling of different pollen species requires an expert biologist to classify particles by sight, and is therefore time-consuming and expensive. Here, an automatic process is developed which segments the particle contour and uses the extracted features for the classification process. We consider shape features, texture features and aperture features and analyze which are useful. The texture features analyzed include: Gabor Filters, Fast Fourier Transform, Local Binary Patterns, Histogram of Oriented Gradients, and Haralick features. We have s…
Integrazione di celle fotovoltaiche ibride nel vetromattone
2012
L’invenzione riguarda l’integrazione del vetromattone con celle solari ibride (organiche/inorganiche), conosciute come Dye-sensitized Solar Cell (DSC). La combinazione del vetromattone con le DSC consente di migliorare le prestazioni del prodotto originario rendendolo in grado di produrre energia pulita. Le caratteristiche di trasparenza e isolamento termo-acustico del prodotto possono essere regolate agendo sulla configurazione delle DSC. Il prodotto può essere assemblato a formare pannelli fotovoltaici per la realizzazione di facciate traslucide energeticamente “attive” in varie condizioni luminose (condizioni di luce diffusa o artificiale) e indipendentemente dall’angolo di radiazione so…
Canopy Architecture Appraisal by Fractal Dimension of 'Flordastar' Peach Trees Grafted onto Different Rootstocks
2007
The objective of this research was to evaluate the modification of canopy architecture of ''Flordastar'' peach (Prunus persica L. Batsch) grafted onto rootstocks with different vigour, by the use of fractal dimension (D). The hypothesis was that different vigour rootstocks are able to modify the complexity of the branching pattern and that this effect can be assessed by a geometric parameter such as the fractal dimension (D) of the 2D projection of tree branching structure. The observations were carried out in a four-year-old experimental orchard of cv. ''Flordastar'' peach trees grafted onto Ishtara, Barrier, GF677 and MrS 2/5 rootstocks. On digital pictures of leafless, dormant peach tree…
A solution to the stochastic point location problem in metalevel nonstationary environments.
2008
This paper reports the first known solution to the stochastic point location (SPL) problem when the environment is nonstationary. The SPL problem involves a general learning problem in which the learning mechanism (which could be a robot, a learning automaton, or, in general, an algorithm) attempts to learn a "parameter," for example, lambda*, within a closed interval. However, unlike the earlier reported results, we consider the scenario when the learning is to be done in a nonstationary setting. For each guess, the environment essentially informs the mechanism, possibly erroneously (i.e., with probability p), which way it should move to reach the unknown point. Unlike the results availabl…
Increasing the Inference and Learning Speed of Tsetlin Machines with Clause Indexing
2020
The Tsetlin Machine (TM) is a machine learning algorithm founded on the classical Tsetlin Automaton (TA) and game theory. It further leverages frequent pattern mining and resource allocation principles to extract common patterns in the data, rather than relying on minimizing output error, which is prone to overfitting. Unlike the intertwined nature of pattern representation in neural networks, a TM decomposes problems into self-contained patterns, represented as conjunctive clauses. The clause outputs, in turn, are combined into a classification decision through summation and thresholding, akin to a logistic regression function, however, with binary weights and a unit step output function. …
Text Compression Using Antidictionaries
1999
International audience; We give a new text compression scheme based on Forbidden Words ("antidictionary"). We prove that our algorithms attain the entropy for balanced binary sources. They run in linear time. Moreover, one of the main advantages of this approach is that it produces very fast decompressors. A second advantage is a synchronization property that is helpful to search compressed data and allows parallel compression. Our algorithms can also be presented as "compilers" that create compressors dedicated to any previously fixed source. The techniques used in this paper are from Information Theory and Finite Automata.