Fractal analysis of the effect of particle aggregation distribution on thermal conductivity of nanofluids

This project was supported by the National Natural Science Foundation of China (No. 41572116), the Fundamental Research Funds for the Central Universities, China University of Geosciences, Wuhan) (No. CUG160602).

Segmentation hiérarchique du domaine sémantique pour l'accélération d'un modèle de langage

Mémoire numérisé par la Direction des bibliothèques de l'Université de Montréal.

Segmentation hiérarchique du domaine sémantique pour l'accélération d'un modèle de langage

Mémoire numérisé par la Direction des bibliothèques de l'Université de Montréal.

Multi-scale colorectal tumour segmentation using a novel coarse to fine strategy

This paper addresses the problem of colorectal tumour segmentation in complex real world imagery. For efficient segmentation, a multi-scale strategy is developed for extracting the potentially cancerous region of interest (ROI) based on colour histograms while searching for the best texture resolution. To achieve better segmentation accuracy, we apply a novel bag-of-visual-words method based on rotation invariant raw statistical features and random projection based l2-norm sparse representation to classify tumour areas in histopathology images. Experimental results on 20 real world digital slides demonstrate that the proposed algorithm results in better recognition accuracy than several state of the art segmentation techniques.

Análisis fractal de procesos dimámicos en el océano

Programa de doctorado: Física, Matemáticas, Geología y Clima. La fecha de publicación es la fecha de lectura.

ICTM: an interval tessellation-based model for reliable topographic segmentation

This work introduces a tessellation-based model for the declivity analysis of geographic regions. The analysis of the relief declivity, which is embedded in the rules of the model, categorizes each tessellation cell, with respect to the whole considered region, according to the (positive, negative, null) sign of the declivity of the cell. Such information is represented in the states assumed by the cells of the model. The overall configuration of such cells allows the division of the region into subregions of cells belonging to a same category, that is, presenting the same declivity sign. In order to control the errors coming from the discretization of the region into tessellation cells, or resulting from numerical computations, interval techniques are used. The implementation of the model is naturally parallel since the analysis is performed on the basis of local rules. An immediate application is in geophysics, where an adequate subdivision of geographic areas into segments presenting similar topographic characteristics is often convenient.

Typologie de la flottille chalutière du port de Sète par une méthode de segmentation

This work aims to define a typology of trawler f1eet in Sète, the main fishing harbour along the French Mediterranean coast, using several multivariate analysis methods. The fishing ships taken to account are represented by annual profiles of landing specific compositions. Five fishing strategies have been identified. A segmentation method using symbolic objects allows a formaI characterisation of the different strategies. These strategies are studied according to several general characteristics usually used for management rules elaboration (power, length, ship age). The typological analysis allows to characterise two main exploitation ways, one directed to the catch of a few species (Engraulis encrasicolus, Sardina pilchardus), the other characterised by the exploitation of a great diversity of species. By this way, it is possible to estimate how the catch of low represented species can significantly contribute to the exploitation of a resource.

Automatic Glaucoma Detection Based on Optic Disc Segmentation and Texture Feature Extraction

The use of digital image processing techniques is prominent in medical settings for the automatic diagnosis of diseases. Glaucoma is the second leading cause of blindness in the world and it has no cure. Currently, there are treatments to prevent vision loss, but the disease must be detected in the early stages. Thus, the objective of this work is to develop an automatic detection method of Glaucoma in retinal images. The methodology used in the study were: acquisition of image database, Optic Disc segmentation, texture feature extraction in different color models and classification of images in glaucomatous or not. We obtained results of 93% accuracy

Réseau calculant asynchrone dédié à la segmentation d'images

National audience

Deep convolutional neural networks for semantic video object segmentation

In this thesis, we propose to infer pixel-level labelling in video by utilising only object category information, exploiting the intrinsic structure of video data. Our motivation is the observation that image-level labels are much more easily to be acquired than pixel-level labels, and it is natural to find a link between the image level recognition and pixel level classification in video data, which would transfer learned recognition models from one domain to the other one. To this end, this thesis proposes two domain adaptation approaches to adapt the deep convolutional neural network (CNN) image recognition model trained from labelled image data to the target domain exploiting both semantic evidence learned from CNN, and the intrinsic structures of unlabelled video data. Our proposed approaches explicitly model and compensate for the domain adaptation from the source domain to the target domain which in turn underpins a robust semantic object segmentation method for natural videos. We demonstrate the superior performance of our methods by presenting extensive evaluations on challenging datasets comparing with the state-of-the-art methods.

Una introducci?n a la geometr?a fractal a trav?s del tratamiento de la autosimilitud integrando un ambiente de geometr?a din?mica

Los desarrollos que se dan en la geometr?a a partir de propuestas como la de B. Mandelbrot y que dan lugar al desarrollo de estructuras fractales son del inter?s para que en este trabajo de grado se pretenda abordar la visualizaci?n como un proceso que influye en el pensamiento, desde el acercamiento que se hace a la geometr?a fractal. Particularmente como los estudiantes de grado noveno entienden un objeto fractal desde la visualizaci?n del mismo, a partir de situaciones did?cticas que consideren algunas construcciones que se destacan en el contexto de la geometr?a fractal, entre las que encontramos el conjunto de Cantor, el tri?ngulo de Sierpinski y la curva de Koch. Sin dejar de lado la importancia que se le brinda a la llegada de las nuevas tecnolog?as de la informaci?n a las aulas y que en educaci?n podr?an ser generadoras de numerosas expectativas respecto al conocimiento.

Text segmentation using a cache memory

International audience