Local and Global Feature Extraction for Invariant Object Recognition

Perceiving the world visually is a basic act for humans, but for computers it is still an unsolved problem. The variability present innatural environments is an obstacle for effective computer vision. The goal of invariant object recognition is to recognise objects in a digital image despite variations in, for example, pose, lighting or occlusion. In this study, invariant object recognition is considered from the viewpoint of feature extraction. Thedifferences between local and global features are studied with emphasis on Hough transform and Gabor filtering based feature extraction. The methods are examined with respect to four capabilities: generality, invariance, stability, and efficiency. Invariant features are presented using both Hough transform and Gabor filtering. A modified Hough transform technique is also presented where the distortion tolerance is increased by incorporating local information. In addition, methods for decreasing the computational costs of the Hough transform employing parallel processing and local information are introduced.

Definition of linear color models in the RGB vector color space to detect red peaches in orchard images taken under natural illumination

This work proposes the detection of red peaches in orchard images based on the definition of different linear color models in the RGB vector color space. The classification and segmentation of the pixels of the image is then performed by comparing the color distance from each pixel to the different previously defined linear color models. The methodology proposed has been tested with images obtained in a real orchard under natural light. The peach variety in the orchard was the paraguayo (Prunus persica var. platycarpa) peach with red skin. The segmentation results showed that the area of the red peaches in the images was detected with an average error of 11.6%; 19.7% in the case of bright illumination; 8.2% in the case of low illumination; 8.6% for occlusion up to 33%; 12.2% in the case of occlusion between 34 and 66%; and 23% for occlusion above 66%. Finally, a methodology was proposed to estimate the diameter of the fruits based on an ellipsoidal fitting. A first diameter was obtained by using all the contour pixels and a second diameter was obtained by rejecting some pixels of the contour. This approach enables a rough estimate of the fruit occlusion percentage range by comparing the two diameter estimates.

Modelling additional costs caused by a new product feature

Työn tavoitteena oli mallintaa uuden tuoteominaisuuden aiheuttamat lisäkustannukset ja suunnitella päätöksenteon työkalu Timberjack Oy:n kuormatraktorivalmistuksen johtoryhmälle. Tarkoituksena oli luoda karkean tason malli, joka sopisi eri tyyppisten tuoteominaisuuksien kustannuksien selvittämiseen. Uuden tuoteominaisuuden vaikutusta yrityksen eri toimintoihin selvitettiin haastatteluin. Haastattelukierroksen tukena käytettiin kysymyslomaketta. Haastattelujen tavoitteena oli selvittää prosessit, toiminnot ja resurssit, jotka ovat välttämättömiä uuden tuoteominaisuuden tuotantoon saattamisessa ja tuotannossa. Malli suunniteltiin haastattelujen ja tietojärjestelmästä hankitun tiedon pohjalta. Mallin rungon muodostivat ne prosessit ja toiminnot, joihin uudella tuoteominaisuudella on vaikutusta. Huomioon otettiin sellaiset resurssit, joita uusi tuoteominaisuus kuluttaa joko välittömästi, tai välillisesti. Tarkasteluun sisällytettiin ainoastaan lisäkustannukset. Uuden tuoteominaisuuden toteuttamisesta riippumattomat, joka tapauksessa toteutuvat yleiskustannukset jätettiin huomioimatta. Malli on yleistys uuden tuoteominaisuuden aiheuttamista lisäkustannuksista, koska tarkoituksena on, että se sopii eri tyyppisten tuoteominaisuuksien aiheuttamien kustannusten selvittämiseen. Lisäksi malli soveltuu muiden pienehköjen tuotemuutosten kustannusten kartoittamiseen.

Reducción del vector de características de reconocimiento facial

In this present work, we are proposing a characteristics reduction system for a facial biometric identification system, using transformed domains such as discrete cosine transformed (DCT) and discrete wavelets transformed (DWT) as parameterization; and Support Vector Machines (SVM) and Neural Network (NN) as classifiers. The size reduction has been done with Principal Component Analysis (PCA) and with Independent Component Analysis (ICA). This system presents a similar success results for both DWT-SVM system and DWT-PCA-SVM system, about 98%. The computational load is improved on training mode due to the decreasing of input’s size and less complexity of the classifier.

Feature Selection, Ranking of Each Feature and Classification for the Diagnosis of Community Acquired Legionella Pneumonia

Diagnosis of community acquired legionella pneumonia (CALP) is currently performed by means of laboratory techniques which may delay diagnosis several hours. To determine whether ANN can categorize CALP and non-legionella community-acquired pneumonia (NLCAP) and be standard for use by clinicians, we prospectively studied 203 patients with community-acquired pneumonia (CAP) diagnosed by laboratory tests. Twenty one clinical and analytical variables were recorded to train a neural net with two classes (LCAP or NLCAP class). In this paper we deal with the problem of diagnosis, feature selection, and ranking of the features as a function of their classification importance, and the design of a classifier the criteria of maximizing the ROC (Receiving operating characteristics) area, which gives a good trade-off between true positives and false negatives. In order to guarantee the validity of the statistics; the train-validation-test databases were rotated by the jackknife technique, and a multistarting procedure was done in order to make the system insensitive to local maxima.

Interleukin-1- and type I interferon-dependent enhanced immunogenicity of an NYVAC-HIV-1 Env-Gag-Pol-Nef vaccine vector with dual deletions of type I and type II interferon-binding proteins.

UNLABELLED: NYVAC, a highly attenuated, replication-restricted poxvirus, is a safe and immunogenic vaccine vector. Deletion of immune evasion genes from the poxvirus genome is an attractive strategy for improving the immunogenic properties of poxviruses. Using systems biology approaches, we describe herein the enhanced immunological profile of NYVAC vectors expressing the HIV-1 clade C env, gag, pol, and nef genes (NYVAC-C) with single or double deletions of genes encoding type I (ΔB19R) or type II (ΔB8R) interferon (IFN)-binding proteins. Transcriptomic analyses of human monocytes infected with NYVAC-C, NYVAC-C with the B19R deletion (NYVAC-C-ΔB19R), or NYVAC-C with B8R and B19R deletions (NYVAC-C-ΔB8RB19R) revealed a concerted upregulation of innate immune pathways (IFN-stimulated genes [ISGs]) of increasing magnitude with NYVAC-C-ΔB19R and NYVAC-C-ΔB8RB19R than with NYVAC-C. Deletion of B8R and B19R resulted in an enhanced activation of IRF3, IRF7, and STAT1 and the robust production of type I IFNs and of ISGs, whose expression was inhibited by anti-type I IFN antibodies. Interestingly, NYVAC-C-ΔB8RB19R induced the production of much higher levels of proinflammatory cytokines (tumor necrosis factor [TNF], interleukin-6 [IL-6], and IL-8) than NYVAC-C or NYVAC-C-ΔB19R as well as a strong inflammasome response (caspase-1 and IL-1β) in infected monocytes. Top network analyses showed that this broad response mediated by the deletion of B8R and B19R was organized around two upregulated gene expression nodes (TNF and IRF7). Consistent with these findings, monocytes infected with NYVAC-C-ΔB8RB19R induced a stronger type I IFN-dependent and IL-1-dependent allogeneic CD4(+) T cell response than monocytes infected with NYVAC-C or NYVAC-C-ΔB19R. Dual deletion of type I and type II IFN immune evasion genes in NYVAC markedly enhanced its immunogenic properties via its induction of the increased expression of type I IFNs and IL-1β and make it an attractive candidate HIV vaccine vector. IMPORTANCE: NYVAC is a replication-deficient poxvirus developed as a vaccine vector against HIV. NYVAC expresses several genes known to impair the host immune defenses by interfering with innate immune receptors, cytokines, or interferons. Given the crucial role played by interferons against viruses, we postulated that targeting the type I and type II decoy receptors used by poxvirus to subvert the host innate immune response would be an attractive approach to improve the immunogenicity of NYVAC vectors. Using systems biology approaches, we report that deletion of type I and type II IFN immune evasion genes in NYVAC poxvirus resulted in the robust expression of type I IFNs and interferon-stimulated genes (ISGs), a strong activation of the inflammasome, and upregulated expression of IL-1β and proinflammatory cytokines. Dual deletion of type I and type II IFN immune evasion genes in NYVAC poxvirus improves its immunogenic profile and makes it an attractive candidate HIV vaccine vector.

Dynamically generated resonances from the vector octet-baryon octet interaction

We study the interaction of vector mesons with the octet of stable baryons in the framework of the local hidden gauge formalism using a coupled channels unitary approach. We examine the scattering amplitudes and their poles, which can be associated to known J P = 1/2- , 3/2- baryon resonances, in some cases, or give predictions in other ones. The formalism employed produces doublets of degenerate J P = 1/2- , 3/2- states, a pattern which is observed experimentally in several cases. The findings of this work should also be useful to guide present experimental programs searching for new resonances, in particular in the strange sector where the current information is very poor.

Signs of a vector's adaptive choice: on the evasion of infectious hosts and parasite-induced mortality

Laboratory and field experiments have demonstrated in many cases that malaria vectors do not feed randomly, but show important preferences either for infected or non-infected hosts. These preferences are likely in part shaped by the costs imposed by the parasites on both their vertebrate and dipteran hosts. However, the effect of changes in vector behaviour on actual parasite transmission remains a debated issue. We used the natural associations between a malaria-like parasite Polychromophilus murinus, the bat fly Nycteribia kolenatii and a vertebrate host the Daubenton's bat Myotis daubentonii to test the vector's feeding preference based on the host's infection status using two different approaches: 1) controlled behavioural assays in the laboratory where bat flies could choose between a pair of hosts; 2) natural bat fly abundance data from wild-caught bats, serving as an approximation of realised feeding preference of the bat flies. Hosts with the fewest infectious stages of the parasite were most attractive to the bat flies that did switch in the behavioural assay. In line with the hypothesis of costs imposed by parasites on their vectors, bat flies carrying parasites had higher mortality. However, in wild populations, bat flies were found feeding more based on the bat's body condition, rather than its infection level. Though the absolute frequency of host switches performed by the bat flies during the assays was low, in the context of potential parasite transmission they were extremely high. The decreased survival of infected bat flies suggests that the preference for less infected hosts is an adaptive trait. Nonetheless, other ecological processes ultimately determine the vector's biting rate and thus transmission. Inherent vector preferences therefore play only a marginal role in parasite transmission in the field. The ecological processes rather than preferences per se need to be identified for successful epidemiological predictions.

Generalization transitions in Hidden-Layer neural networks for third-order feature discrimination

Stochastic learning processes for a specific feature detector are studied. This technique is applied to nonsmooth multilayer neural networks requested to perform a discrimination task of order 3 based on the ssT-block¿ssC-block problem. Our system proves to be capable of achieving perfect generalization, after presenting finite numbers of examples, by undergoing a phase transition. The corresponding annealed theory, which involves the Ising model under external field, shows good agreement with Monte Carlo simulations.

Genomic insights into the Ixodes scapularis tick vector of Lyme disease.

Ticks transmit more pathogens to humans and animals than any other arthropod. We describe the 2.1 Gbp nuclear genome of the tick, Ixodes scapularis (Say), which vectors pathogens that cause Lyme disease, human granulocytic anaplasmosis, babesiosis and other diseases. The large genome reflects accumulation of repetitive DNA, new lineages of retro-transposons, and gene architecture patterns resembling ancient metazoans rather than pancrustaceans. Annotation of scaffolds representing ∼57% of the genome, reveals 20,486 protein-coding genes and expansions of gene families associated with tick-host interactions. We report insights from genome analyses into parasitic processes unique to ticks, including host 'questing', prolonged feeding, cuticle synthesis, blood meal concentration, novel methods of haemoglobin digestion, haem detoxification, vitellogenesis and prolonged off-host survival. We identify proteins associated with the agent of human granulocytic anaplasmosis, an emerging disease, and the encephalitis-causing Langat virus, and a population structure correlated to life-history traits and transmission of the Lyme disease agent.

Resurrecting Disney: Tracing Walt Disney‘s ever-present spirit in feature animated films of the Michael Eisner era (1984-2004)

El treball Ressuscitant a Disney: Rastrejant el sempre present esperit de Walt Disney en els llargmetratges animats de l'era Michael Eisner (1984-2004) pretén definir i analitzar les característiques, tant respecte al procés creatiu com en la definició de contingut, integrades en els clàssics originals de Disney per, a continuació, demostrar que aquestes van ser recuperades i implementades de nou després de la mort de Walt Disney -amb lleus adaptacions- per donar lloc a una segona edat d'or de l'animació

Shared feature extraction for nearest neighbor face recognition

In this paper, we propose a new supervised linearfeature extraction technique for multiclass classification problemsthat is specially suited to the nearest neighbor classifier (NN).The problem of finding the optimal linear projection matrix isdefined as a classification problem and the Adaboost algorithmis used to compute it in an iterative way. This strategy allowsthe introduction of a multitask learning (MTL) criterion in themethod and results in a solution that makes no assumptions aboutthe data distribution and that is specially appropriated to solvethe small sample size problem. The performance of the methodis illustrated by an application to the face recognition problem.The experiments show that the representation obtained followingthe multitask approach improves the classic feature extractionalgorithms when using the NN classifier, especially when we havea few examples from each class

A Sparse Bayesian Approach for Joint Feature Selection and Classifier Learning

Peer-reviewed