1,187 research outputs found
Deep Learning for Semantic Part Segmentation with High-Level Guidance
In this work we address the task of segmenting an object into its parts, or
semantic part segmentation. We start by adapting a state-of-the-art semantic
segmentation system to this task, and show that a combination of a
fully-convolutional Deep CNN system coupled with Dense CRF labelling provides
excellent results for a broad range of object categories. Still, this approach
remains agnostic to high-level constraints between object parts. We introduce
such prior information by means of the Restricted Boltzmann Machine, adapted to
our task and train our model in an discriminative fashion, as a hidden CRF,
demonstrating that prior information can yield additional improvements. We also
investigate the performance of our approach ``in the wild'', without
information concerning the objects' bounding boxes, using an object detector to
guide a multi-scale segmentation scheme. We evaluate the performance of our
approach on the Penn-Fudan and LFW datasets for the tasks of pedestrian parsing
and face labelling respectively. We show superior performance with respect to
competitive methods that have been extensively engineered on these benchmarks,
as well as realistic qualitative results on part segmentation, even for
occluded or deformable objects. We also provide quantitative and extensive
qualitative results on three classes from the PASCAL Parts dataset. Finally, we
show that our multi-scale segmentation scheme can boost accuracy, recovering
segmentations for finer parts.Comment: 11 pages (including references), 3 figures, 2 table
Use of the Crop Circleâ„¢ sensor to estimate peanut (Arachis hypogaea L.) best maturity time for harvesting
Political budget cycles and reelection prospects in Greece's municipalities
This paper considers the presence of political budget cycles in Greece's municipalities. We construct a new dataset from primary sources and we find strong evidence of pre-electoral manipulation through increased expenditures and excessive borrowing. We use a dynamic panel data approach producing evidence of opportunistic behavior in local government finances. Our results are robust in the face of a series of controls including mayors running for reelection, their political alignment with the central government, and prolonged terms. Moreover, the results are robust to the exclusion of small sized municipalities and to the restriction of the time range of our investigation to the post-Maastricht period. We also consider whether opportunistic policies influence incumbents' reelection prospects finding that increased expenditures and election year opportunistic excesses are electorally rewarding. Our findings provide a characterization of opportunistic public finance management in Greek municipalities where electorally motivated budgetary decisions appear impervious to the various municipal reform attempts
An integrated assessment framework for the analysis of multiple pressures in aquatic ecosystems and the appraisal of management options
The contribution illustrates an integrated assessment framework aimed at evaluating the relationships between multiple pressures and water body status for the purposes of river basin management. The framework includes the following steps. (1) Understanding how the different pressures affect the status of water bodies. This entails the characterization of biophysical state variables and the definition of a causal relationship between pressures and status. Therefore this step involves interaction between experts bearing ecological understanding and experts providing models to represent the effect of pressures. (2) Identifying the relevant pressures to be addressed through appropriate measures to improve the status of water bodies. (3) Evaluating reduction targets for the relevant pressures identified in a river basin, by weighting the effort associated to reducing individual pressures and the potential benefits in terms of water body status. (4) Designing management measures through a creative process and political discussion of alternative options, balancing costs, benefits and effectiveness based on engineering and economic analysis. (5) Simulating scenarios of implementation of a programme of measures in order to check their effectiveness and robustness against climate and land use change. We discuss the five steps of the assessment framework, and particularly the interaction between science and policy at the different stages. We review the assessment tools required at each step and, for setting optimal pressure reduction targets (step 3), we propose and illustrate a simplified multicriteria approach based on semi-quantitative assessment, which produces frontiers of optimal trade-offs between effort spent on measures, and achievements
Charging and Discharging Processes in AlN Dielectric Films Deposited by Plasma Assisted Molecular Beam Epitaxy
In the present work the electrical properties of AlN polycrystalline films deposited at low temperatures by plasma-assisted molecular beam epitaxy (PA-MBE) are investigated. The polarization build-up during constant current injection as well as the depolarization process after the current stress have been investigated through monitoring voltage transients in Metal – Insulator – Metal (MIM) capacitors, in temperature range from 300 K to 400 K. Moreover, current – voltage characteristics obtained at different temperatures revealed that charge collection at low fields in these films occurs through variable range hopping
GABRB3 mutations: a new and emerging cause of early infantile epileptic encephalopathy
The gamma-aminobutyric acid type A receptor β3 gene (GABRB3) encodes the β3-subunit of the gamma-aminobutyric acid type A (GABAA ) receptor, which mediates inhibitory signalling within the central nervous system. Recently, GABRB3 mutations have been identified in a few patients with infantile spasms and Lennox-Gastaut syndrome. We report the clinical and electrographic features of a novel case of GABRB3-related early-onset epileptic encephalopathy. Our patient presented with neonatal hypotonia and feeding difficulties, then developed pharmacoresistant epileptic encephalopathy, characterized by multiple seizure types from 3 months of age. Electroencephalography demonstrated ictal generalized and interictal multifocal epileptiform abnormalities. Using a SureSelectXT custom multiple gene panel covering 48 early infantile epileptic encephalopathy/developmental delay genes, a novel de novo GABRB3 heterozygous missense mutation, c.860C>T (p.Thr287Ile), was identified and confirmed on Sanger sequencing. GABRB3 is an emerging cause of early-onset epilepsy. Novel genetic technologies, such as whole-exome/genome sequencing and multiple gene panels, will undoubtedly identify further cases, allowing more detailed electroclinical delineation of the GABRB3-related genotypic and phenotypic spectra
Accumulation-based computing using phasechange memories with FET access devices
Copyright © 2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.Phase-change materials and devices have received much attention as a potential route to the realization of various types of unconventional computing paradigms. In this letter, we present non-von Neumann arithmetic processing that exploits the accumulative property of phase-change memory (PCM) cells. Using PCM cells with integrated FET access devices, we perform a detailed study of accumulation-based computation. We also demonstrate efficient factorization using PCM cells, a technique that could pave the way for massively parallelized computations.Engineering and Physical Sciences Research Council (EPSRC
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