Search results for " Computer Science"
showing 10 items of 3983 documents
Active learning in a real-world bioengineering problem: A pilot-study on ophthalmologic data processing
2019
Active learning is a format alternative to the conventional lecture/recitation/laboratory; research results have reported that it is suitable to encourage student inquiry and foster peer mentoring. Although the availability of computer-based learning materials in biomedical sciences is increasing, there are relatively few studies aimed to integrate traditional methods of teaching with inquiry-based approaches utilizing these Information and Communication Technologies (ICT) tools. This paper describes a pilot-study on a comprehensive active laboratory course about digital ophthalmologic signal classification, experienced by a group of undergraduates in Bio-Electronic Engineering. During the …
A Special Issue on Advances in Machine Learning for Remote Sensing and Geosciences [From the Guest Editors]
2016
Machine learning has become a standard paradigm for the analysis of remote sensing and geoscience data at both local and global scales. In the upcoming years, with the advent of new satellite constellations, machine learning will have a fundamental role in processing large and heterogeneous data sources. Machine learning will move from mere statistical data processing to actual learning, understanding, and knowledge extraction. The ambitious goal is to provide responses to the challenging scientific questions about the earth system. This special issue aims at providing an updated, refreshing view of current developments in the field. For this special issue, we have collected five articles t…
New results for finding common neighborhoods in massive graphs in the data stream model
2008
AbstractWe consider the problem of finding pairs of vertices that share large common neighborhoods in massive graphs. We give lower bounds for randomized, two-sided error algorithms that solve this problem in the data-stream model of computation. Our results correct and improve those of Buchsbaum, Giancarlo, and Westbrook [On finding common neighborhoods in massive graphs, Theoretical Computer Science, 299 (1–3) 707–718 (2004)]
Reverse-Safe Text Indexing
2021
We introduce the notion of reverse-safe data structures. These are data structures that prevent the reconstruction of the data they encode (i.e., they cannot be easily reversed). A data structure D is called z - reverse-safe when there exist at least z datasets with the same set of answers as the ones stored by D . The main challenge is to ensure that D stores as many answers to useful queries as possible, is constructed efficiently, and has size close to the size of the original dataset it encodes. Given a text of length n and an integer z , we propose an algorithm that constructs a z -reverse-safe data structure ( z -RSDS) that has size O(n) and answers decision and counting pattern matc…
Exudate-based diabetic macular edema detection in fundus images using publicly available datasets
2010
International audience; Diabetic macular edema (DME) is a common vision threatening complication of diabetic retinopathy. In a large scale screening environment DME can be assessed by detecting exudates (a type of bright lesions) in fundus images. In this work, we introduce a new methodology for diagnosis of DME using a novel set of features based on colour, wavelet decomposition and automatic lesion segmentation. These features are employed to train a classifier able to automatically diagnose DME through the presence of exudation. We present a new publicly available dataset with ground-truth data containing 169 patients from various ethnic groups and levels of DME. This and other two publi…
Iterative Symmetry Detection: Shrinking vs. Decimating Patterns
2005
This paper introduces a new mechanism that consists of applying a symmetry operator on an iteratively transformed version of the input image. The nature of the transformation characterizes the operator. Here, we consider the Object Symmetry Transform combined with the morphological operator erosion and the pyramid decimation respectively. The derived operators have been applied on both binary and gray levels images, comparing their ability to grasp the internal structure of a digital object. We present some experiments to evaluate their performances and check them for result quality versus computing complexity.
Integrated Computer-Aided Innovation: The PROSIT approach
2009
Abstract The paper presents a methodology aimed at the improvement of the product development cycle through the integration of Computer-Aided Innovation (CAI) with Optimization and PLM systems. The interoperability of these tools is obtained through the adoption of Optimization systems as a bridging element between CAI and PLM systems. This methodology was developed within the PROSIT project ( http://www.kaemart.it/prosit ). The paper describes the main issues related to the integration of these complementary instruments and the solutions proposed by the authors. More specifically, the main idea of the PROSIT project to link CAI and Optimization systems is the adoption of the latter tools n…
LC3: A spatio-temporal and semantic model for knowledge discovery from geospatial datasets
2015
International audience; There is a need for decision-makers to be provided with both an overview of existing knowledge, and information which is as complete and up-to-date as possible on changes in certain features of the biosphere. Another objective is to bring together all the many attempts which have been made over the years at various levels (international, Community, national and regional) to obtain more information on the environment and the way it is changing. As a result, remote sensing tools monitor large amount of land cover informations enabling study of dynamic processes. However the size of the dataset require new tools to identify pattern and extract knowledge. We propose a mo…
Verbal ordinal classification with multicriteria decision aiding
2008
Abstract Professionals in neuropsychology usually perform diagnoses of patients’ behaviour in a verbal rather than in a numerical form. This fact generates interest in decision support systems that process verbal data. It also motivates us to develop methods for the classification of such data. In this paper, we describe ways of aiding classification of a discrete set of objects, evaluated on set of criteria that may have verbal estimations, into ordered decision classes. In some situations, there is no explicit additional information available, while in others it is possible to order the criteria lexicographically. We consider both of these cases. The proposed Dichotomic Classification (DC…
Reference point approach for multiple decision makers
2005
We consider multiple criteria decision-making problems where a group of decision-makers wants to find the most preferred solution from a discrete set of alternatives. We develop a method that uses achievement functions for charting subsets of reference points that would support a certain alternative to be the most preferred one. The resulting descriptive information is provided to the decision-makers in the form of reference acceptability indices and central reference points for each decision alternative. Then, the decision-makers can compare this information with their own preferences. We demonstrate the use of the method using a strategic multiple criteria decision model for an electricit…