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Variance components for egg production traits (No of eggs produced between 19 and 26, 26 and 38 and 26 and 54 wk of age), egg characteristics (average egg weight at 2 different ages and egg density) and body weight of hens at 40 wk of age were estimated in two strains of a breeding company by univariate and multivariate Restricted Maximum Likelihood (REML)(More)
Breeding programmes described as community-based (CBBP) typically relate to low-input systems with farmers having a common interest to improve and share their genetic resources. CBBPs are more frequent with keepers of small ruminants, in particular smallholders of local breeds, than with cattle, pigs or chickens with which farmers may have easier access to(More)
SUMMARY In multiple trait animal model evaluations, several transformations (canonical, triangular, combined) can be used to decrease the size of the mixed model equations or to increase their sparsity. A simple method based on an EM argument and replacing missing records by their expectation given the current parameters allows the use of the canonical(More)
This paper describes a road obstacle classification system that recognizes both vehicles and pedestrians in far-infrared images. Different local and global features based on Speeded Up Robust Features (SURF) were investigated and then selected in order to extract a discriminative signature from the infrared spectrum. First, local features representing the(More)
One of the main challenges in Intelligent Vehicle is recognition of road obstacles. Our goal is to design a real-time, precise and robust pedestrian recognition system. We choose to use Speeded Up Robust Features (SURF) and a Support Vector Machine (SVM) classifier in order to perform the recognition task. Our main contribution is a method for fast(More)
Pedestrian detection is an important but challenging component of an Intelligent Transportation System. In this paper, we describe a pedestrian detection system based on a monocular vision with a Far-Infrared camera (FIR). We propose an original feature representation, called Intensity Self Similarity (ISS), adapted to pedestrian detection in FIR images.(More)
In this work, we focus on an improvement of a road obstacle recognition system using SVM based classifiers combination. The improvement relies on the use of Dempster-Shafer theory (DST) to combine in a finer way the outputs of SVM classifiers. The SVM classifiers were trained on different local and global features based on Speeded Up Robust Features (SURF)(More)
One of the main challenges in intelligent vehicles concerns pedestrian detection for driving assistance. Recent experiments have showed that state-of-the-art descriptors provide better performances on the far-infrared (FIR) spectrum than on the visible one, even in daytime conditions, for pedestrian classification. In this paper, we propose a pedestrian(More)
The performance of an object recognition system depends on both object representation and classification algorithms. On the one hand, Object representation by using local descriptors have become a very powerful representation of images. On the other hand, SVM has shown impressive learning and recognition performances. In this paper, we present a method for(More)