Search results for "methodologie"
showing 10 items of 2141 documents
Prey-predator strategies in a multiagent system
2006
This paper describes the prey-predator multiagent system which can be considered as an abstraction of more complex real-world models. Both the prey and the predators are considered as autonomous agents with their own behaviors and perception of the environment. In particular, we propose a simulator which lets study different strategies such as cooperation and individualism. An extensive experiment has been carried out in order to prove the effectiveness of the latter.
High temperature solid-catalized transesterification for biodiesel production
2010
Biodiesel has become more attractive recently because of its environmental benefits and the fact that it is made from renewable resources. Biodiesel is a mixture of monoalkyl esters of long chain fatty acids derived from renewable feed stock like vegetable oils and animal fats, mainly made of fatty acid glycerides. It is produced by transesterification processes in which oil or fat are reacted with a monohydric alcohol in the presence of a catalyst. The transesterification process is affected by reaction conditions, alcohol to oil molar ratio, type of alcohol, type and amount of catalysts, temperature and purity of reactants. Heterogeneous acid catalysts are quite efficient in promoting the…
Background subtraction for aerial surveillance conditions
2014
International audience; The first step in a surveillance system is to create a representation of the environment. Background subtraction is widely used algorithm to define a part of an image that most time remains stationary in a video. In surveillance tasks, this model helps to recognize those outlier objects in an area under monitoring. Set up a background model on moving platforms (intelligent cars, UAVs, etc.) is a challenging task due camera motion when images are acquired. In this paper, we propose a method to support instabilities caused by aerial images fusing spatial and temporal information about image motion. We used frame difference as first approximation, then age of pixels is …
CUSHAW2-GPU: Empowering Faster Gapped Short-Read Alignment Using GPU Computing
2014
We present CUSHAW2-GPU to accelerate the CUSHAW2 algorithm using compute unified device architecture (CUDA)-enabled GPUs. Two critical GPU computing techniques, namely intertask hybrid CPU-GPU parallelism and tile-based Smith-Waterman map backtracking using CUDA, are investigated to facilitate fast alignments. By aligning both simulated and real reads to the human genome, our aligner yields comparable or better performance compared to BWA-SW, Bowtie2, and GEM. Furthermore, CUSHAW2-GPU with a Tesla K20c GPU achieves significant speedups over the multithreaded CUSHAW2, BWA-SW, Bowtie2, and GEM on the 12 cores of a high-end CPU for both single-end and paired-end alignment.
An adaptive-PCA algorithm for reflectance estimation from color images
2008
This paper deals with the problem of spectral reflectance estimation from color camera outputs. Because the reconstruction of such functions is an inverse problem, stabilizing the reconstruction process is highly desirable. One way to do this is to decompose reflectance function on a basis functions like PCA. The present work proposes an algorithm making PCA adaptive in reflectance estimation from a color camera output. We propose to adapt the PCA basis derivation by selecting, for each sample, the more relevant elements from the training set elements. The adaptivity criterion is achieved by a likelihood measurement. Finally, the spectral reflectance estimation results are evaluated with th…
Reflectance-based surface saliency
2017
In this paper, we propose an original methodology allowing the computation of the saliency maps for high dimensional RTI data (Reflectance Transformation Imaging). Unlike most of the classical methods, our approach aims at devising an intrinsic visual saliency of the surface, independent of the sensor (image) and the geometry of the scene (light-object-camera). From RTI data, we use the DMD (Discrete Modal Decomposition) technique for the angular reflectance reconstruction, which we extend by a new transformation on the modal basis enabling a rotation-invariant representation of reconstructed reflectances. This orientation-invariance of the resulting reflectance shapes fosters a robust esti…
Restoration of out-of-focus images based on circle of confusion estimate
2002
In this paper a new method for a fast out-of-focus blur estimation and restoration is proposed. It is suitable for CFA (Color Filter Array) images acquired by typical CCD/CMOS sensor. The method is based on the analysis of a single image and consists of two steps: 1) out-of-focus blur estimation via Bayer pattern analysis; 2) image restoration. Blur estimation is based on a block-wise edge detection technique. This edge detection is carried out on the green pixels of the CFA sensor image also called Bayer pattern. Once the blur level has been estimated the image is restored through the application of a new inverse filtering technique. This algorithm gives sharp images reducing ringing and c…
Image Processing Chain For Digital Still Cameras Based On The Simpil Architecture
2005
The new generation of wireless devices herald the development of products for integrated portable image and video communication requiring to image and video applications high computing performance. Portable MultiMedia Supercomputers (PMMS), a new class of architectures, allow to combine high computational performance, needed by multimedia applications, and a big energy efficiency, needed by portable devices. Among PMMS, the SIMPil (SIMD processor pixel) architecture satisfies the above requirements, especially with video and digital images processing tasks. In this paper we, exploit the SIMPil computation and throughput efficiency to implement the whole image processing chain of a digital s…
Big Data in metagenomics: Apache Spark vs MPI.
2020
The progress of next-generation sequencing has lead to the availability of massive data sets used by a wide range of applications in biology and medicine. This has sparked significant interest in using modern Big Data technologies to process this large amount of information in distributed memory clusters of commodity hardware. Several approaches based on solutions such as Apache Hadoop or Apache Spark, have been proposed. These solutions allow developers to focus on the problem while the need to deal with low level details, such as data distribution schemes or communication patterns among processing nodes, can be ignored. However, performance and scalability are also of high importance when…
Cluster-based active learning for compact image classification
2010
In this paper, we consider active sampling to label pixels grouped with hierarchical clustering. The objective of the method is to match the data relationships discovered by the clustering algorithm with the user's desired class semantics. The first is represented as a complete tree to be pruned and the second is iteratively provided by the user. The active learning algorithm proposed searches the pruning of the tree that best matches the labels of the sampled points. By choosing the part of the tree to sample from according to current pruning's uncertainty, sampling is focused on most uncertain clusters. This way, large clusters for which the class membership is already fixed are no longer…