Search results for " Informatica"
showing 10 items of 978 documents
Estimating the Best Reference Homography for Planar Mosaics From Videos
2015
This paper proposes a novel strategy to find the best reference homography in mosaics from video sequences. The reference homography globally minimizes the distortions induced on each image frame by the mosaic homography itself. This method is designed for planar mosaics on which a bad choice of the first reference image frame can lead to severe distortions after concatenating several successive homographies. This often happens in the case of underwater mosaics with non-flat seabed and no georeferential information available. Given a video sequence of an almost planar surface, sub-mosaics with low distortions of temporally close image frames are computed and successively merged according to…
Importance of force feedback for following uneven virtual paths with a stylus
2021
It is commonly known that a physical textured path can be followed by indirect touch through a probe also in absence of vision if sufficiently informative cues are delivered by the other sensory channels, but prior research indicates that the level of performance while following a virtual path on a touchscreen depends on the type and channel such cues belong to. The re-enactment of oriented forces, as they are induced by localized obstacles in probe-based exploration, may be important to equalize the performance between physical and virtual path following. Using a stylus attached to a force-feedback arm, an uneven path marked by virtual bars was traversed while time and positions were measu…
Interval Length Analysis in Multi Layer Model
2009
In this paper we present an hypothesis test of randomness based on the probability density function of the symmetrized Kulback-Leibler distance estimated, via a Monte Carlo simulation, by the distributions of the interval lengths detected using the Multi-Layer Model (MLM). The $MLM$ is based on the generation of several sub-samples of an input signal; in particular a set of optimal cut-set thresholds are applied to the data to detect signal properties. In this sense MLM is a general pattern detection method and it can be considered a preprocessing tool for pattern discovery. At the present the test has been evaluated on simulated signals which respect a particular tiled microarray approach …
A novel framework for MR image segmentation and quantification by using MedGA
2019
BACKGROUND AND OBJECTIVES: Image segmentation represents one of the most challenging issues in medical image analysis to distinguish among different adjacent tissues in a body part. In this context, appropriate image pre-processing tools can improve the result accuracy achieved by computer-assisted segmentation methods. Taking into consideration images with a bimodal intensity distribution, image binarization can be used to classify the input pictorial data into two classes, given a threshold intensity value. Unfortunately, adaptive thresholding techniques for two-class segmentation work properly only for images characterized by bimodal histograms. We aim at overcoming these limitations and…
Computer-Assisted Approaches for Uterine Fibroid Segmentation in MRgFUS Treatments: Quantitative Evaluation and Clinical Feasibility Analysis
2019
Nowadays, uterine fibroids can be treated using Magnetic Resonance guided Focused Ultrasound Surgery (MRgFUS), which is a non-invasive therapy exploiting thermal ablation. In order to measure the Non-Perfused Volume (NPV) for treatment response assessment, the ablated fibroid areas (i.e., Region of Treatment, ROT) are manually contoured by a radiologist. The current operator-dependent methodology could affect the subsequent follow-up phases, due to the lack of result repeatability. In addition, this fully manual procedure is time-consuming, considerably increasing execution times. These critical issues can be addressed only by means of accurate and efficient automated Pattern Recognition ap…
An Iconic Framework for Learning the Art of Programming
2016
The integration of programming teachings, in all levels of education, highlights the need to acquire the art of programming for each individual student through versatile tools based on specific cognitive methods. Diversified linguistic metaphors have to be adopted by the developing frame, in order to highlight the qualities of each student. Therefore, a framework, oriented to learning the art of programming, must foster polychrome constructs representations, a number of data structures and an intuitive interfaces in order to make easier to understand the evolution of the algorithm that have to be developed. The following contribution will present a theoretical formalization of a framework f…
Deep Metric Learning for Transparent Classification of Covid-19 X-Ray Images
2022
This work proposes an interpretable classifier for automatic Covid-19 classification using chest X-ray images. It is based on a deep learning model, in particular, a triplet network, devoted to finding an effective image embedding. Such embedding is a non-linear projection of the images into a space of reduced dimension, where homogeneity and separation of the classes measured by a predefined metric are improved. A K-Nearest Neighbor classifier is the interpretable model used for the final classification. Results on public datasets show that the proposed methodology can reach comparable results with state of the art in terms of accuracy, with the advantage of providing interpretability to t…
Image segmentation to evaluate islets of langherans
2008
This contribution deals with an unsupervised system to process digital photomicrographs in order to locate and analyze islets of Langherans in human pancreases. The experiment has been conducted on real data and, though we are still going to complete the evaluation of the whole method, we expect to define a set of proper features (e.g. area, perimeter, fractal dimension, shape complexity, texture and entropy) useful for a fast and reliable counting of healthy cells. In particular, this research aims to measure the advisability of a possible implantation in patients affected by type I diabetes mellitus
Dissecting and Reassembling Color Correction Algorithms for Image Stitching
2018
This paper introduces a new compositional framework for classifying color correction methods according to their two main computational units. The framework was used to dissect fifteen among the best color correction algorithms and the computational units so derived, with the addition of four new units specifically designed for this work, were then reassembled in a combinatorial way to originate about one hundred distinct color correction methods, most of which never considered before. The above color correction methods were tested on three different existing datasets, including both real and artificial color transformations, plus a novel dataset of real image pairs categorized according to …
Learned Sorted Table Search and Static Indexes in Small-Space Data Models
2023
Machine-learning techniques, properly combined with data structures, have resulted in Learned Static Indexes, innovative and powerful tools that speed up Binary Searches with the use of additional space with respect to the table being searched into. Such space is devoted to the machine-learning models. Although in their infancy, these are methodologically and practically important, due to the pervasiveness of Sorted Table Search procedures. In modern applications, model space is a key factor, and a major open question concerning this area is to assess to what extent one can enjoy the speeding up of Binary Searches achieved by Learned Indexes while using constant or nearly constant-space mod…