This paper presents a novel segmentation algorithm which automatically learns the combination of weak segmenters and builds a strong one based on the assumption that the locally weighted combination varies w.r.t. both the weak segmenters and the training images. We learn the weighted combination during the training stage using a discriminative spatial regularization which depends on training se...

• Summary.-Low-speed tests have been carried out on a family of three single-stage compressors of different diameter ratios. The simple blade design tested showed considerable variations of performance as the diameter ratio was decreased from 0.65 to 0.35 but most of these variations are predictable by simple means and it is expected that they may be partially avoided by appropriate design meth...

We propose an estimation procedure for linear functionals based on Gaussian model selection techniques. We show that the procedure is adaptive, and we give a non asymptotic oracle inequality for the risk of the selected estimator with respect to the Lp loss. An application to the problem of estimating a signal or its r derivative at a given point is developed and minimax rates are proved to hol...

Rate allocation has become a demanding task in data networks as diversity in users and traffics proliferate. Most commonly used algorithm in end hosts is TCP. This is a loss based scheme therefore it exhibits oscillatory behavior which reduces network performance. Moreover, since the price for all sessions is based on the aggregate throughput, losses that are caused by TCP affect other sessions...

In this paper, a Bayesian approach is proposed for shift point detection in an inverse Gaussian distribution. In this study, the mean parameter of inverse Gaussian distribution is assumed to be constant and shift points in shape parameter is considered. First the posterior distribution of shape parameter is obtained. Then the Bayes estimators are derived under a class of priors and using variou...

In the main paper, we have reviewed variants of AIPs according to the loss functions and the optimisation algorithms. Algorithms FGV, FGS, BI, and GA use the softmax-log loss − log f̂ . The DeepFool (DF) and our GAMAN variants use the difference of two scores (e.g. f ? − f). This section includes an auxiliary analysis for the effect of the loss type: softmax-log loss− log f̂ versus score loss −f ...

carcass yield is important economical parameters for producers and contributors of meat science. in the present study, carcass yield and also the weight losses resulted post mortem until consumption were investigated. the mean values of cold carcass and hot carcass weight were 15.63 and 15.33, the mean value of cooling loss was 1.87% and average value of hot and cold efficiency were 41.44% and ...

1 BACKGROUND In the last three decades various researchers had been facing the problem of maximizing global network performances by optimizing traffic signals. The main difficulty of the problem arises from the existing interaction between network performance and users' route choice. In fact, drivers make their travel choices in order to minimize their own travel time. Simultaneous choices perf...