1,386 research outputs found
Multi-view Face Detection Using Deep Convolutional Neural Networks
In this paper we consider the problem of multi-view face detection. While
there has been significant research on this problem, current state-of-the-art
approaches for this task require annotation of facial landmarks, e.g. TSM [25],
or annotation of face poses [28, 22]. They also require training dozens of
models to fully capture faces in all orientations, e.g. 22 models in HeadHunter
method [22]. In this paper we propose Deep Dense Face Detector (DDFD), a method
that does not require pose/landmark annotation and is able to detect faces in a
wide range of orientations using a single model based on deep convolutional
neural networks. The proposed method has minimal complexity; unlike other
recent deep learning object detection methods [9], it does not require
additional components such as segmentation, bounding-box regression, or SVM
classifiers. Furthermore, we analyzed scores of the proposed face detector for
faces in different orientations and found that 1) the proposed method is able
to detect faces from different angles and can handle occlusion to some extent,
2) there seems to be a correlation between dis- tribution of positive examples
in the training set and scores of the proposed face detector. The latter
suggests that the proposed methods performance can be further improved by using
better sampling strategies and more sophisticated data augmentation techniques.
Evaluations on popular face detection benchmark datasets show that our
single-model face detector algorithm has similar or better performance compared
to the previous methods, which are more complex and require annotations of
either different poses or facial landmarks.Comment: in International Conference on Multimedia Retrieval 2015 (ICMR
Quantitative test of the barrier nucleosome model for statistical positioning of nucleosomes up- and downstream of transcription start sites
The positions of nucleosomes in eukaryotic genomes determine which parts of
the DNA sequence are readily accessible for regulatory proteins and which are
not. Genome-wide maps of nucleosome positions have revealed a salient pattern
around transcription start sites, involving a nucleosome-free region (NFR)
flanked by a pronounced periodic pattern in the average nucleosome density.
While the periodic pattern clearly reflects well-positioned nucleosomes, the
positioning mechanism is less clear. A recent experimental study by Mavrich et
al. argued that the pattern observed in S. cerevisiae is qualitatively
consistent with a `barrier nucleosome model', in which the oscillatory pattern
is created by the statistical positioning mechanism of Kornberg and Stryer. On
the other hand, there is clear evidence for intrinsic sequence preferences of
nucleosomes, and it is unclear to what extent these sequence preferences affect
the observed pattern. To test the barrier nucleosome model, we quantitatively
analyze yeast nucleosome positioning data both up- and downstream from NFRs.
Our analysis is based on the Tonks model of statistical physics which
quantifies the interplay between the excluded-volume interaction of nucleosomes
and their positional entropy. We find that although the typical patterns on the
two sides of the NFR are different, they are both quantitatively described by
the same physical model, with the same parameters, but different boundary
conditions. The inferred boundary conditions suggest that the first nucleosome
downstream from the NFR (the +1 nucleosome) is typically directly positioned
while the first nucleosome upstream is statistically positioned via a
nucleosome-repelling DNA region. These boundary conditions, which can be
locally encoded into the genome sequence, significantly shape the statistical
distribution of nucleosomes over a range of up to ~1000 bp to each side.Comment: includes supporting materia
Statistical M-Estimation and Consistency in Large Deformable Models for Image Warping
The problem of defining appropriate distances between shapes or images and modeling the variability of natural images by group transformations is at the heart of modern image analysis. A current trend is the study of probabilistic and statistical aspects of deformation models, and the development of consistent statistical procedure for the estimation of template images. In this paper, we consider a set of images randomly warped from a mean template which has to be recovered. For this, we define an appropriate statistical parametric model to generate random diffeomorphic deformations in two-dimensions. Then, we focus on the problem of estimating the mean pattern when the images are observed with noise. This problem is challenging both from a theoretical and a practical point of view. M-estimation theory enables us to build an estimator defined as a minimizer of a well-tailored empirical criterion. We prove the convergence of this estimator and propose a gradient descent algorithm to compute this M-estimator in practice. Simulations of template extraction and an application to image clustering and classification are also provided
Efficacy and safety of single 40 mg/kg oral praziquantel in the treatment of schistosomiasis in preschool-age versus school-age children:An individual participant data meta-analysis
Better knowledge of the efficacy and safety of single 40 mg/kg oral praziquantel in preschool-age children is required, should preventive chemotherapy programs for schistosomiasis be expanded to include this age group.; We analyzed individual participant-level data from 16 studies (13 single-arm or cohort studies and three randomized trials), amounting to 683 preschool-age children (aged <6 years) and 2,010 school-age children (aged 6-14 years). Children had a documented Schistosoma mansoni or S. haematobium infection, were treated with single 40 mg/kg oral praziquantel, and assessed between 21 and 60 days post-treatment. Efficacy was expressed as arithmetic mean and individual egg reduction rate (ERR) and meta-analyzed using general linear models and mixed models. Safety was summarized using reported adverse events (AEs).; Preschool-age children had significantly lower baseline Schistosoma egg counts and more losses to follow-up compared to school-age children. No difference in efficacy was found between preschool- and school-age children using a general linear model of individual-participant ERR with baseline log-transformed egg count as covariate and study, age, and sex as fixed variables, and a mixed model with a random effect on the study. Safety was reported in only four studies (n = 1,128 individuals); few AEs were reported in preschool-age children 4 and 24 hours post-treatment as well as at follow-up. Three severe but not serious AEs were recorded in school-age children during follow-up.; There is no indication that single 40 mg/kg oral praziquantel would be less efficacious and safe in preschool-age children compared to school-age children, with the caveat that only few randomized comparisons exist between the two age groups. Preventive chemotherapy might therefore be extended to preschool-age children, with proper monitoring of its efficacy and safety
Teacher evaluation in Portugal: persisting challenges and perceived effects
This paper reports on findings from a broader piece of research aimed at investigating the ways in which head teachers experience a new teacher evaluation policy in Portugal, particularly in regard to the challenges and perceived effects of the policy on school and on teacher development. Data were collected through a questionnaire with open and closed-ended questions. In total, 134 head teachers participated in the study. Findings suggest a number of tensions and problems, most of which are related to the key features of the model of teacher evaluation itself. Others issues pertain to the lack of recognition of the appraisers and to the emergence of tensions amongst staff leading to the deterioration of the school climate. Persisting challenges to policy implementation, perceived effects on teachers and schools as well as the dilemmas of head teachers are analysed. The article concludes with the discussion of ways forward.Financial Support by CIEC (Research Centre on Child Studies, IE, UMinho; FCT R&D unit 317, Portugal) by the Strategic Project UID/CED/00317/2013, with financial support of National Funds through the FCT (Foundation for Science and Technology) and co-financed by European Regional Development Funds (FEDER) through the COMPETE 2020 - Competitiveness and Internationalization Operational Program (POCI) with the reference POCI-01-0145-FEDER-00756
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