Results 61 to 70 of about 9,151,209 (331)
Densely Supervised Grasp Detector (DSGD)
, 2019 This paper presents Densely Supervised Grasp Detector (DSGD), a deep learning framework which combines CNN structures with layer-wise feature fusion and produces grasps and their confidence scores at different levels of the image hierarchy (i.e., global-,
Asif, Umar +2 more
core +1 more source
Confidence Intervals and Upper Bounds for Small Signals in the Presence of Background Noise [PDF]
, 2000 We discuss a new method for setting limits on small signals in the presence of background noise. The method is based on a combination of a two dimensional confidence region and the large sample approximation to the likelihood ratio test statistic.
Angel M. López +8 more
core +3 more sources
Determination of the joint confidence region of the optimal operating conditions in robust design by the bootstrap technique [PDF]
International Journal of Production Research, 2012 Robust design is widely recognised as a leading method for reducing variability and improving quality. Most of the engineering statistics literature focuses on finding point estimates of the optimum operating conditions for robust design.
Chanseok Park
semanticscholar +1 more source
MathematicsThe receiver operating characteristic (ROC) curve is a valuable statistical tool in medical research. It assesses a biomarker’s ability to distinguish between diseased and healthy individuals.
Siyan Liu +3 more
doaj +1 more source
Smoothed and Iterated Bootstrap Confidence Regions for Parameter Vectors [PDF]
, 2013 The construction of confidence regions for parameter vectors is a difficult problem in the nonparametric setting, particularly when the sample size is not large.
Ghosh, Santu, Polansky, Alan M.
core
Journal of the Royal Statistical Society Series B: Statistical Methodology, 1964 Summary To test a hypothesis that a parameter has value θ* we usually ask whether an observation falls in a critical region of the outcome space. It is well known that, by a suitable choice of confidence region, an equivalent test is to ask whether θ* lies outside the confidence region.
openaire +2 more sources
Asymptotic properties of SPS confidence regions [PDF]
Automatica, 2017 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Weyer, Erik +2 more
openaire +2 more sources
Semantic Segmentation Refinement by Monte Carlo Region Growing of High Confidence Detections [PDF]
Asian Conference on Computer Vision, 2018 Despite recent improvements using fully convolutional networks, in general, the segmentation produced by most state-of-the-art semantic segmentation methods does not show satisfactory adherence to the object boundaries.
P. Dias, Henry Medeiros
semanticscholar +1 more source
Pediatric Blood &Cancer, EarlyView.ABSTRACT Background Families of children with cancer experience significant financial strain, even with universal healthcare. Indirect costs, such as productivity losses and non‐medical expenses, are rarely included in economic evaluations, and little is known about how effectively financial aid programmes alleviate this burden. Childhood brain tumours
Megumi Lim +8 more
wiley +1 more source
Empirical likelihood inference for threshold autoregressive conditional heteroscedasticity model
Journal of Inequalities and Applications, 2021 This paper considers the parameter estimation problem of a first-order threshold autoregressive conditional heteroscedasticity model by using the empirical likelihood method.
Cuixin Peng, Zhiwen Zhao
doaj +1 more source