913 resultados para Reconstruction kernel


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We study the action of a weighted Fourier–Laplace transform on the functions in the reproducing kernel Hilbert space (RKHS) associated with a positive definite kernel on the sphere. After defining a notion of smoothness implied by the transform, we show that smoothness of the kernel implies the same smoothness for the generating elements (spherical harmonics) in the Mercer expansion of the kernel. We prove a reproducing property for the weighted Fourier–Laplace transform of the functions in the RKHS and embed the RKHS into spaces of smooth functions. Some relevant properties of the embedding are considered, including compactness and boundedness. The approach taken in the paper includes two important notions of differentiability characterized by weighted Fourier–Laplace transforms: fractional derivatives and Laplace–Beltrami derivatives.

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The importance of mechanical aspects related to cell activity and its environment is becoming more evident due to their influence in stem cell differentiation and in the development of diseases such as atherosclerosis. The mechanical tension homeostasis is related to normal tissue behavior and its lack may be related to the formation of cancer, which shows a higher mechanical tension. Due to the complexity of cellular activity, the application of simplified models may elucidate which factors are really essential and which have a marginal effect. The development of a systematic method to reconstruct the elements involved in the perception of mechanical aspects by the cell may accelerate substantially the validation of these models. This work proposes the development of a routine capable of reconstructing the topology of focal adhesions and the actomyosin portion of the cytoskeleton from the displacement field generated by the cell on a flexible substrate. Another way to think of this problem is to develop an algorithm to reconstruct the forces applied by the cell from the measurements of the substrate displacement, which would be characterized as an inverse problem. For these kind of problems, the Topology Optimization Method (TOM) is suitable to find a solution. TOM is consisted of an iterative application of an optimization method and an analysis method to obtain an optimal distribution of material in a fixed domain. One way to experimentally obtain the substrate displacement is through Traction Force Microscopy (TFM), which also provides the forces applied by the cell. Along with systematically generating the distributions of focal adhesion and actin-myosin for the validation of simplified models, the algorithm also represents a complementary and more phenomenological approach to TFM. As a first approximation, actin fibers and flexible substrate are represented through two-dimensional linear Finite Element Method. Actin contraction is modeled as an initial stress of the FEM elements. Focal adhesions connecting actin and substrate are represented by springs. The algorithm was applied to data obtained from experiments regarding cytoskeletal prestress and micropatterning, comparing the numerical results to the experimental ones

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[EN] The information provided by the International Commission for the Conservation of Atlantic Tunas (ICCAT) on captures of skipjack tuna (Katsuwonus pelamis) in the central-east Atlantic has a number of limitations, such as gaps in the statistics for certain fleets and the level of spatiotemporal detail at which catches are reported. As a result, the quality of these data and their effectiveness for providing management advice is limited. In order to reconstruct missing spatiotemporal data of catches, the present study uses Data INterpolating Empirical Orthogonal Functions (DINEOF), a technique for missing data reconstruction, applied here for the first time to fisheries data. DINEOF is based on an Empirical Orthogonal Functions decomposition performed with a Lanczos method. DINEOF was tested with different amounts of missing data, intentionally removing values from 3.4% to 95.2% of data loss, and then compared with the same data set with no missing data. These validation analyses show that DINEOF is a reliable methodological approach of data reconstruction for the purposes of fishery management advice, even when the amount of missing data is very high.

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[EN] In this paper we present a variational technique for the reconstruction of 3D cylindrical surfaces. Roughly speaking by a cylindrical surface we mean a surface that can be parameterized using the projection on a cylinder in terms of two coordinates, representing the displacement and angle in a cylindrical coordinate system respectively. The starting point for our method is a set of different views of a cylindrical surface, as well as a precomputed disparity map estimation between pair of images. The proposed variational technique is based on an energy minimization where we balance on the one hand the regularity of the cylindrical function given by the distance of the surface points to cylinder axis, and on the other hand, the distance between the projection of the surface points on the images and the expected location following the precomputed disparity map estimation between pair of images. One interesting advantage of this approach is that we regularize the 3D surface by means of a bi-dimensio al minimization problem. We show some experimental results for large stereo sequences.

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[EN] In this work, we present a new model for a dense disparity estimation and the 3-D geometry reconstruction using a color image stereo pair. First, we present a brief introduction to the 3-D Geometry of a camera system. Next, we propose a new model for the disparity estimation based on an energy functional. We look for the local minima of the energy using the associate Euler-Langrage partial differential equations. This model is a generalization to color image of the model developed in, with some changes in the strategy to avoid the irrelevant local minima. We present some numerical experiences of 3-D reconstruction, using this method some real stereo pairs.

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[EN] In this paper, we present a vascular tree model made with synthetic materials and which allows us to obtain images to make a 3D reconstruction.We have used PVC tubes of several diameters and lengths that will let us evaluate the accuracy of our 3D reconstruction. In order to calibrate the camera we have used a corner detector. Also we have used Optical Flow techniques to follow the points through the images going and going back. We describe two general techniques to extract a sequence of corresponding points from multiple views of an object. The resulting sequence of points will be used later to reconstruct a set of 3D points representing the object surfaces on the scene. We have made the 3D reconstruction choosing by chance a couple of images and we have calculated the projection error. After several repetitions, we have found the best 3D location for the point.

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[EN] In this paper, we present a vascular tree model made with synthetic materials and which allows us to obtain images to make a 3D reconstruction. In order to create this model, we have used PVC tubes of several diameters and lengths that will let us evaluate the accuracy of our 3D reconstruction. We have made the 3D reconstruction from a series of images that we have from our model and after we have calibrated the camera. In order to calibrate it we have used a corner detector. Also we have used Optical Flow techniques to follow the points through the images going and going back. Once we have the set of images where we have located a point, we have made the 3D reconstruction choosing by chance a couple of images and we have calculated the projection error. After several repetitions, we have found the best 3D location for the point.

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[EN] In the last years we have developed some methods for 3D reconstruction. First we began with the problem of reconstructing a 3D scene from a stereoscopic pair of images. We developed some methods based on energy functionals which produce dense disparity maps by preserving discontinuities from image boundaries. Then we passed to the problem of reconstructing a 3D scene from multiple views (more than 2). The method for multiple view reconstruction relies on the method for stereoscopic reconstruction. For every pair of consecutive images we estimate a disparity map and then we apply a robust method that searches for good correspondences through the sequence of images. Recently we have proposed several methods for 3D surface regularization. This is a postprocessing step necessary for smoothing the final surface, which could be afected by noise or mismatch correspondences. These regularization methods are interesting because they use the information from the reconstructing process and not only from the 3D surface. We have tackled all these problems from an energy minimization approach. We investigate the associated Euler-Lagrange equation of the energy functional, and we approach the solution of the underlying partial differential equation (PDE) using a gradient descent method.

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[EN]A study on the recent history and current state of the aquifer in the Island of Gran Canaria (Canary Is., 28oN, 15oW) is performed. Though rainfall is scarce on the island, traditional agricultural practices and small population were able to keep the aquifer in a constant state for centuries. Nevertheless, at the beginning of the 20th Century, culture of several water-consuming species was introduced on a commercial basis due to the relative proximity of the Canaries to continental Europe and to the possibility of more than one yearly harvest. This led to generalised well digging (more than 300m deep in many cases) and to the appearance of a chronic hydraulic deficit, as well as to spoiling vastcoastal areas of the aquifer through intrusion of brackish water. In the mid 1960’s, coincident with the apex of agricultural exploitation, massive tourism appeared in the scene. This new activity soon became a susbstitute for Agriculture, but it attracted more new labour force to the island, and a fast growth of population was the main result. Moreover, new water use practices entered the scene. As a consequence, the main causes for the aquifer decline are population growth and extensive Agriculture practices in use during the last half of the 20th Century. Some remarks on sustainability issues in order to cope with Climate Change are also offered.

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L’analisi del movimento umano ha come obiettivo la descrizione del movimento assoluto e relativo dei segmenti ossei del soggetto e, ove richiesto, dei relativi tessuti molli durante l’esecuzione di esercizi fisici. La bioingegneria mette a disposizione dell’analisi del movimento gli strumenti ed i metodi necessari per una valutazione quantitativa di efficacia, funzione e/o qualità del movimento umano, consentendo al clinico l’analisi di aspetti non individuabili con gli esami tradizionali. Tali valutazioni possono essere di ausilio all’analisi clinica di pazienti e, specialmente con riferimento a problemi ortopedici, richiedono una elevata accuratezza e precisione perché il loro uso sia valido. Il miglioramento della affidabilità dell’analisi del movimento ha quindi un impatto positivo sia sulla metodologia utilizzata, sia sulle ricadute cliniche della stessa. Per perseguire gli obiettivi scientifici descritti, è necessario effettuare una stima precisa ed accurata della posizione e orientamento nello spazio dei segmenti ossei in esame durante l’esecuzione di un qualsiasi atto motorio. Tale descrizione può essere ottenuta mediante la definizione di un modello della porzione del corpo sotto analisi e la misura di due tipi di informazione: una relativa al movimento ed una alla morfologia. L’obiettivo è quindi stimare il vettore posizione e la matrice di orientamento necessari a descrivere la collocazione nello spazio virtuale 3D di un osso utilizzando le posizioni di punti, definiti sulla superficie cutanea ottenute attraverso la stereofotogrammetria. Le traiettorie dei marker, così ottenute, vengono utilizzate per la ricostruzione della posizione e dell’orientamento istantaneo di un sistema di assi solidale con il segmento sotto esame (sistema tecnico) (Cappozzo et al. 2005). Tali traiettorie e conseguentemente i sistemi tecnici, sono affetti da due tipi di errore, uno associato allo strumento di misura e l’altro associato alla presenza di tessuti molli interposti tra osso e cute. La propagazione di quest’ultimo ai risultati finali è molto più distruttiva rispetto a quella dell’errore strumentale che è facilmente minimizzabile attraverso semplici tecniche di filtraggio (Chiari et al. 2005). In letteratura è stato evidenziato che l’errore dovuto alla deformabilità dei tessuti molli durante l’analisi del movimento umano provoca inaccuratezze tali da mettere a rischio l’utilizzabilità dei risultati. A tal proposito Andriacchi scrive: “attualmente, uno dei fattori critici che rallentano il progresso negli studi del movimento umano è la misura del movimento scheletrico partendo dai marcatori posti sulla cute” (Andriacchi et al. 2000). Relativamente alla morfologia, essa può essere acquisita, ad esempio, attraverso l’utilizzazione di tecniche per bioimmagini. Queste vengono fornite con riferimento a sistemi di assi locali in generale diversi dai sistemi tecnici. Per integrare i dati relativi al movimento con i dati morfologici occorre determinare l’operatore che consente la trasformazione tra questi due sistemi di assi (matrice di registrazione) e di conseguenza è fondamentale l’individuazione di particolari terne di riferimento, dette terne anatomiche. L’identificazione di queste terne richiede la localizzazione sul segmento osseo di particolari punti notevoli, detti repere anatomici, rispetto ad un sistema di riferimento solidale con l’osso sotto esame. Tale operazione prende il nome di calibrazione anatomica. Nella maggior parte dei laboratori di analisi del movimento viene implementata una calibrazione anatomica a “bassa risoluzione” che prevede la descrizione della morfologia dell’osso a partire dall’informazione relativa alla posizione di alcuni repere corrispondenti a prominenze ossee individuabili tramite palpazione. Attraverso la stereofotogrammetria è quindi possibile registrare la posizione di questi repere rispetto ad un sistema tecnico. Un diverso approccio di calibrazione anatomica può essere realizzato avvalendosi delle tecniche ad “alta risoluzione”, ovvero attraverso l’uso di bioimmagini. In questo caso è necessario disporre di una rappresentazione digitale dell’osso in un sistema di riferimento morfologico e localizzare i repere d’interesse attraverso palpazione in ambiente virtuale (Benedetti et al. 1994 ; Van Sint Jan et al. 2002; Van Sint Jan et al. 2003). Un simile approccio è difficilmente applicabile nella maggior parte dei laboratori di analisi del movimento, in quanto normalmente non si dispone della strumentazione necessaria per ottenere le bioimmagini; inoltre è noto che tale strumentazione in alcuni casi può essere invasiva. Per entrambe le calibrazioni anatomiche rimane da tenere in considerazione che, generalmente, i repere anatomici sono dei punti definiti arbitrariamente all’interno di un’area più vasta e irregolare che i manuali di anatomia definiscono essere il repere anatomico. L’identificazione dei repere attraverso una loro descrizione verbale è quindi povera in precisione e la difficoltà nella loro identificazione tramite palpazione manuale, a causa della presenza dei tessuti molli interposti, genera errori sia in precisione che in accuratezza. Tali errori si propagano alla stima della cinematica e della dinamica articolare (Ramakrishnan et al. 1991; Della Croce et al. 1999). Della Croce (Della Croce et al. 1999) ha inoltre evidenziato che gli errori che influenzano la collocazione nello spazio delle terne anatomiche non dipendono soltanto dalla precisione con cui vengono identificati i repere anatomici, ma anche dalle regole che si utilizzano per definire le terne. E’ infine necessario evidenziare che la palpazione manuale richiede tempo e può essere effettuata esclusivamente da personale altamente specializzato, risultando quindi molto onerosa (Simon 2004). La presente tesi prende lo spunto dai problemi sopra elencati e ha come obiettivo quello di migliorare la qualità delle informazioni necessarie alla ricostruzione della cinematica 3D dei segmenti ossei in esame affrontando i problemi posti dall’artefatto di tessuto molle e le limitazioni intrinseche nelle attuali procedure di calibrazione anatomica. I problemi sono stati affrontati sia mediante procedure di elaborazione dei dati, sia apportando modifiche ai protocolli sperimentali che consentano di conseguire tale obiettivo. Per quanto riguarda l’artefatto da tessuto molle, si è affrontato l’obiettivo di sviluppare un metodo di stima che fosse specifico per il soggetto e per l’atto motorio in esame e, conseguentemente, di elaborare un metodo che ne consentisse la minimizzazione. Il metodo di stima è non invasivo, non impone restrizione al movimento dei tessuti molli, utilizza la sola misura stereofotogrammetrica ed è basato sul principio della media correlata. Le prestazioni del metodo sono state valutate su dati ottenuti mediante una misura 3D stereofotogrammetrica e fluoroscopica sincrona (Stagni et al. 2005), (Stagni et al. 2005). La coerenza dei risultati raggiunti attraverso i due differenti metodi permette di considerare ragionevoli le stime dell’artefatto ottenute con il nuovo metodo. Tale metodo fornisce informazioni sull’artefatto di pelle in differenti porzioni della coscia del soggetto e durante diversi compiti motori, può quindi essere utilizzato come base per un piazzamento ottimo dei marcatori. Lo si è quindi utilizzato come punto di partenza per elaborare un metodo di compensazione dell’errore dovuto all’artefatto di pelle che lo modella come combinazione lineare degli angoli articolari di anca e ginocchio. Il metodo di compensazione è stato validato attraverso una procedura di simulazione sviluppata ad-hoc. Relativamente alla calibrazione anatomica si è ritenuto prioritario affrontare il problema associato all’identificazione dei repere anatomici perseguendo i seguenti obiettivi: 1. migliorare la precisione nell’identificazione dei repere e, di conseguenza, la ripetibilità dell’identificazione delle terne anatomiche e della cinematica articolare, 2. diminuire il tempo richiesto, 3. permettere che la procedura di identificazione possa essere eseguita anche da personale non specializzato. Il perseguimento di tali obiettivi ha portato alla implementazione dei seguenti metodi: • Inizialmente è stata sviluppata una procedura di palpazione virtuale automatica. Dato un osso digitale, la procedura identifica automaticamente i punti di repere più significativi, nella maniera più precisa possibile e senza l'ausilio di un operatore esperto, sulla base delle informazioni ricavabili da un osso digitale di riferimento (template), preliminarmente palpato manualmente. • E’ stato poi condotto uno studio volto ad indagare i fattori metodologici che influenzano le prestazioni del metodo funzionale nell’individuazione del centro articolare d’anca, come prerequisito fondamentale per migliorare la procedura di calibrazione anatomica. A tale scopo sono stati confrontati diversi algoritmi, diversi cluster di marcatori ed è stata valutata la prestazione del metodo in presenza di compensazione dell’artefatto di pelle. • E’stato infine proposto un metodo alternativo di calibrazione anatomica basato sull’individuazione di un insieme di punti non etichettati, giacenti sulla superficie dell’osso e ricostruiti rispetto ad un TF (UP-CAST). A partire dalla posizione di questi punti, misurati su pelvi coscia e gamba, la morfologia del relativo segmento osseo è stata stimata senza identificare i repere, bensì effettuando un’operazione di matching dei punti misurati con un modello digitale dell’osso in esame. La procedura di individuazione dei punti è stata eseguita da personale non specializzato nell’individuazione dei repere anatomici. Ai soggetti in esame è stato richiesto di effettuare dei cicli di cammino in modo tale da poter indagare gli effetti della nuova procedura di calibrazione anatomica sulla determinazione della cinematica articolare. I risultati ottenuti hanno mostrato, per quel che riguarda la identificazione dei repere, che il metodo proposto migliora sia la precisione inter- che intraoperatore, rispetto alla palpazione convenzionale (Della Croce et al. 1999). E’ stato inoltre riscontrato un notevole miglioramento, rispetto ad altri protocolli (Charlton et al. 2004; Schwartz et al. 2004), nella ripetibilità della cinematica 3D di anca e ginocchio. Bisogna inoltre evidenziare che il protocollo è stato applicato da operatori non specializzati nell’identificazione dei repere anatomici. Grazie a questo miglioramento, la presenza di diversi operatori nel laboratorio non genera una riduzione di ripetibilità. Infine, il tempo richiesto per la procedura è drasticamente diminuito. Per una analisi che include la pelvi e i due arti inferiori, ad esempio, l’identificazione dei 16 repere caratteristici usando la calibrazione convenzionale richiede circa 15 minuti, mentre col nuovo metodo tra i 5 e i 10 minuti.

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[ES]The purpose of this paper was to use threedimensional computed tomographic reconstruction as another tool to teach in the veterinary colleges. 2-millimeters thick transverse images of two foals and one dog were obtained. Images provided excellent detail of relevant anatomic structures and detailed information regarding the extent of disease and accurate discrimination of neoplastic versus non-neoplastic diseases. Tridimensional reconstruction can be a valuable diagnostic aid for clinical evaluation of several disturbances and could be used as a tool for teaching anatomy in veterinary schools.

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A single picture provides a largely incomplete representation of the scene one is looking at. Usually it reproduces only a limited spatial portion of the scene according to the standpoint and the viewing angle, besides it contains only instantaneous information. Thus very little can be understood on the geometrical structure of the scene, the position and orientation of the observer with respect to it remaining also hard to guess. When multiple views, taken from different positions in space and time, observe the same scene, then a much deeper knowledge is potentially achievable. Understanding inter-views relations enables construction of a collective representation by fusing the information contained in every single image. Visual reconstruction methods confront with the formidable, and still unanswered, challenge of delivering a comprehensive representation of structure, motion and appearance of a scene from visual information. Multi-view visual reconstruction deals with the inference of relations among multiple views and the exploitation of revealed connections to attain the best possible representation. This thesis investigates novel methods and applications in the field of visual reconstruction from multiple views. Three main threads of research have been pursued: dense geometric reconstruction, camera pose reconstruction, sparse geometric reconstruction of deformable surfaces. Dense geometric reconstruction aims at delivering the appearance of a scene at every single point. The construction of a large panoramic image from a set of traditional pictures has been extensively studied in the context of image mosaicing techniques. An original algorithm for sequential registration suitable for real-time applications has been conceived. The integration of the algorithm into a visual surveillance system has lead to robust and efficient motion detection with Pan-Tilt-Zoom cameras. Moreover, an evaluation methodology for quantitatively assessing and comparing image mosaicing algorithms has been devised and made available to the community. Camera pose reconstruction deals with the recovery of the camera trajectory across an image sequence. A novel mosaic-based pose reconstruction algorithm has been conceived that exploit image-mosaics and traditional pose estimation algorithms to deliver more accurate estimates. An innovative markerless vision-based human-machine interface has also been proposed, so as to allow a user to interact with a gaming applications by moving a hand held consumer grade camera in unstructured environments. Finally, sparse geometric reconstruction refers to the computation of the coarse geometry of an object at few preset points. In this thesis, an innovative shape reconstruction algorithm for deformable objects has been designed. A cooperation with the Solar Impulse project allowed to deploy the algorithm in a very challenging real-world scenario, i.e. the accurate measurements of airplane wings deformations.

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Stress recovery techniques have been an active research topic in the last few years since, in 1987, Zienkiewicz and Zhu proposed a procedure called Superconvergent Patch Recovery (SPR). This procedure is a last-squares fit of stresses at super-convergent points over patches of elements and it leads to enhanced stress fields that can be used for evaluating finite element discretization errors. In subsequent years, numerous improved forms of this procedure have been proposed attempting to add equilibrium constraints to improve its performances. Later, another superconvergent technique, called Recovery by Equilibrium in Patches (REP), has been proposed. In this case the idea is to impose equilibrium in a weak form over patches and solve the resultant equations by a last-square scheme. In recent years another procedure, based on minimization of complementary energy, called Recovery by Compatibility in Patches (RCP) has been proposed in. This procedure, in many ways, can be seen as the dual form of REP as it substantially imposes compatibility in a weak form among a set of self-equilibrated stress fields. In this thesis a new insight in RCP is presented and the procedure is improved aiming at obtaining convergent second order derivatives of the stress resultants. In order to achieve this result, two different strategies and their combination have been tested. The first one is to consider larger patches in the spirit of what proposed in [4] and the second one is to perform a second recovery on the recovered stresses. Some numerical tests in plane stress conditions are presented, showing the effectiveness of these procedures. Afterwards, a new recovery technique called Last Square Displacements (LSD) is introduced. This new procedure is based on last square interpolation of nodal displacements resulting from the finite element solution. In fact, it has been observed that the major part of the error affecting stress resultants is introduced when shape functions are derived in order to obtain strains components from displacements. This procedure shows to be ultraconvergent and is extremely cost effective, as it needs in input only nodal displacements directly coming from finite element solution, avoiding any other post-processing in order to obtain stress resultants using the traditional method. Numerical tests in plane stress conditions are than presented showing that the procedure is ultraconvergent and leads to convergent first and second order derivatives of stress resultants. In the end, transverse stress profiles reconstruction using First-order Shear Deformation Theory for laminated plates and three dimensional equilibrium equations is presented. It can be seen that accuracy of this reconstruction depends on accuracy of first and second derivatives of stress resultants, which is not guaranteed by most of available low order plate finite elements. RCP and LSD procedures are than used to compute convergent first and second order derivatives of stress resultants ensuring convergence of reconstructed transverse shear and normal stress profiles respectively. Numerical tests are presented and discussed showing the effectiveness of both procedures.

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Machine learning comprises a series of techniques for automatic extraction of meaningful information from large collections of noisy data. In many real world applications, data is naturally represented in structured form. Since traditional methods in machine learning deal with vectorial information, they require an a priori form of preprocessing. Among all the learning techniques for dealing with structured data, kernel methods are recognized to have a strong theoretical background and to be effective approaches. They do not require an explicit vectorial representation of the data in terms of features, but rely on a measure of similarity between any pair of objects of a domain, the kernel function. Designing fast and good kernel functions is a challenging problem. In the case of tree structured data two issues become relevant: kernel for trees should not be sparse and should be fast to compute. The sparsity problem arises when, given a dataset and a kernel function, most structures of the dataset are completely dissimilar to one another. In those cases the classifier has too few information for making correct predictions on unseen data. In fact, it tends to produce a discriminating function behaving as the nearest neighbour rule. Sparsity is likely to arise for some standard tree kernel functions, such as the subtree and subset tree kernel, when they are applied to datasets with node labels belonging to a large domain. A second drawback of using tree kernels is the time complexity required both in learning and classification phases. Such a complexity can sometimes prevents the kernel application in scenarios involving large amount of data. This thesis proposes three contributions for resolving the above issues of kernel for trees. A first contribution aims at creating kernel functions which adapt to the statistical properties of the dataset, thus reducing its sparsity with respect to traditional tree kernel functions. Specifically, we propose to encode the input trees by an algorithm able to project the data onto a lower dimensional space with the property that similar structures are mapped similarly. By building kernel functions on the lower dimensional representation, we are able to perform inexact matchings between different inputs in the original space. A second contribution is the proposal of a novel kernel function based on the convolution kernel framework. Convolution kernel measures the similarity of two objects in terms of the similarities of their subparts. Most convolution kernels are based on counting the number of shared substructures, partially discarding information about their position in the original structure. The kernel function we propose is, instead, especially focused on this aspect. A third contribution is devoted at reducing the computational burden related to the calculation of a kernel function between a tree and a forest of trees, which is a typical operation in the classification phase and, for some algorithms, also in the learning phase. We propose a general methodology applicable to convolution kernels. Moreover, we show an instantiation of our technique when kernels such as the subtree and subset tree kernels are employed. In those cases, Direct Acyclic Graphs can be used to compactly represent shared substructures in different trees, thus reducing the computational burden and storage requirements.