Carlos Rivero

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In this paper, we propose a biologically inspired, global and segmentation free methodology for manuscript noise reduction and classification. Our method consists of developing well-adapted tools for writing enhancement, background noise, text and drawing separation and handwritten patterns characterization with orientation features. We have used here(More)
This paper presents a new system for handwriting documents denoising and indexing. This work is based on the Hermite Transform, which is a polynomial transform and a good model of the human visual system (HVS). We use this transformation to decompose handwriting documents into local frequencies and using this decomposition, we analyze the visual aspect of(More)
This work presents a learning algorithm to reach the optimum action of an arbitrary set of actions contained in IRm. An initial and arbitrary probability measure on IRm allow us to select an action and the probability is sequentially updated by a stochastic automaton using the response of the environment to the selected action. We prove that the(More)
Experience shows that companies consistently underestimate the time and effort to develop complex products quickly. Managers of strategic projects can often anticipate effort to do direct work, but they routinely underestimate effort to coordinate and do rework. Neither managers’ intuitions nor standard project management tools can effectively predict the(More)
Continuing education for health care providers presents an ongoing challenge in an environment of personnel limitations and budget constraints. Learning is a constant requirement for safe and effective health care practice; in addition, it is often a requirement for licensure. The purpose of this article is to review a model of distance learning as a method(More)
Propose a system which uses Program Dependence Graphs as an intermediate representation of codes to perform approximate sub graph isomorphism using graph alignment techniques for finding similar code. The document aims at defining all of the concepts used to build the system along with the results being compared with the current state of the art, JPLAG. The(More)
Acknowledgements I would like to thank Prof Carlos Rivero for his guidance throughout the project and Prof Leon Reznik for his guidance in the colloquium. The paper implemented in the MS capstone project is " Subgraph Matching in with Set Similarity in Large Graph Database " by authors " The report is my understanding of all the methods used in the paper[1](More)