Enhancing Perceptual Attributes with Bayesian Style Generation

Deep learning has brought an unprecedented progress in computer vision and significant advances have been made in predicting subjective properties inherent to visual data (e.g., memorability, aesthetic quality, evoked emotions, etc.). Recently, some research works have even proposed deep learning approaches to modify images such as to appropriately alter these properties. Following this research line, this paper introduces a novel deep learning framework for synthesizing images in order to enhance a predefined perceptual attribute. Our approach takes as input a natural image and exploits recent models for deep style transfer and generative adversarial networks to change its style in order to modify a specific high-level attribute. Differently from previous works focusing on enhancing a specific property of a visual content, we propose a general framework and demonstrate its effectiveness in two use cases, i.e. increasing image memorability and generating scary pictures. We evaluate the proposed approach on publicly available benchmarks, demonstrating its advantages over state of the art methods.Comment: ACCV-201

Totem: a case study in HEP

It is being proved that the neurochip \Totem{} is a viable solution for high quality and real time computational tasks in HEP, including event classification, triggering and signal processing. The architecture of the chip is based on a "derivative free" algorithm called Reactive Tabu Search (RTS), highly performing even for low precision weights. ISA, VME or PCI boards integrate the chip as a coprocessor in a host computer. This paper presents: 1) the state of the art and the next evolution of the design of \Totem{}; 2) its ability in the Higgs search at LHC as an example.Comment: Latex, elsart.sty, 5 pages, talk presented by I.Lazzizzera at CHEP97 (Berlin, April 1997

The charm of structural neuroimaging in insanity evaluations. guidelines to avoid misinterpretation of the findings

Despite the popularity of structural neuroimaging techniques in twenty-first-century research, its results have had limited translational impact in real-world settings, where inferences need to be made at the individual level. Structural neuroimaging methods are now introduced frequently to aid in assessing defendants for insanity in criminal forensic evaluations, with the aim of providing “convergence” of evidence on the mens rea of the defendant. This approach may provide pivotal support for judges’ decisions. Although neuroimaging aims to reduce uncertainty and controversies in legal settings and to increase the objectivity of criminal rulings, the application of structural neuroimaging in forensic settings is hampered by cognitive biases in the evaluation of evidence that lead to misinterpretation of the imaging results. It is thus increasingly important to have clear guidelines on the correct ways to apply and interpret neuroimaging evidence. In the current paper, we review the literature concerning structural neuroimaging in court settings with the aim of identifying rules for its correct application and interpretation. These rules, which aim to decrease the risk of biases, focus on the importance of (i) descriptive diagnoses, (ii) anatomo-clinical correlation, (iii) brain plasticity and (iv) avoiding logical fallacies, such as reverse inference. In addition, through the analysis of real forensic cases, we describe errors frequently observed due to incorrect interpretations of imaging. Clear guidelines for both the correct circumstances for introducing neuroimaging and its eventual interpretation are defined

Geometric invariant theory approach to the determination of ground states of D-wave condensates in isotropic space

A complete and rigorous determination of the possible ground states for D-wave pairing Bose condensates is presented, using a geometrical invariant theory approach to the problem. The order parameter is argued to be a vector, transforming according to a ten dimensional real representation of the group $G=${\bf O}$_3\otimes${\bf U}$_1\times$. We determine the equalities and inequalities defining the orbit space of this linear group and its symmetry strata, which are in a one-to-one correspondence with the possible distinct phases of the system. We find 15 allowed phases (besides the unbroken one), with different symmetries, that we thoroughly determine. The group-subgroup relations between bordering phases are pointed out. The perturbative sixth degree corrections to the minimum of a fourth degree polynomial $G$-invariant free energy, calculated by Mermin, are also determined.Comment: 27 revtex pages, 2 figures, use of texdraw; minor changes in the bibliography and in Table II

Os repositórios educacionais como auxiliares do ensino e suas múltiplas linguagens : vídeos

Neste trabalho é feita uma análise de um repositório educacional virtual: o Portal do Professor. Site governamental lançado pelo Ministério da Educação e da Cultura do Brasil (MEC) em parceria com o Ministério da Ciência e Tecnologia. O portal em questão se propõe a auxiliar a prática docente dos professores da Educação Básica (Educação Infantil, Ensino Fundamental e Médio, que no Brasil compreende crianças e jovens geralmente até os 17 anos). O portal oferece algumas ferramentas digitais, como textos digitais, aplicativos computacionais interativos, elementos visuais como fotos e desenhos, elementos auditivos, como sons, e elementos audiovisuais, foco de estudo deste trabalho. A articulação desses fatores, feita pelo próprio professor, pode resultar em aulas sobre determinado tema, que podem ser postadas e acessadas via internet

Integrated likelihoods in models with stratum nuisance parameters

Inference about a parameter of interest in presence of a nuisance parameter can be based on an integrated likelihood function. We analyze the behaviour of inferential quantities based on such a pseudo-likelihood in a two-index asymptotics framework, in which both sample size and dimension of the nuisance parameter may diverge to infinity. We show that the integrated likelihood, if chosen wisely, largely outperforms standard likelihood methods, such as the profile likelihood. These results are confirmed by simulation studies, in which comparisons with modified profile likelihood are also considered