Search results for "Image"
showing 10 items of 6818 documents
New techniques for visualization of losses due to image compression in grayscale medical still images
2003
To evaluate the visual influence of irreversible compression on medical images, changes of the images have to be visualized. The authors have explored alternative techniques to be used instead of the usual side-by-side comparison, where the information contained in both images is perceived in a single image, preserving the context between compression errors and image structures. Thus fast and easy comparison can be done. These techniques make use of the human ability to perceive information also in the dimensions of color, space, and time. A study was performed with JPEG-compressed coronary angiographic images. Changes in the resulting images for six compression factors from 7 to 30 were sc…
Ultreya, suseya, Santiago!” Viaggio e spazialità ne La ballata dei pellegrini
2020
Per studiare dal punto di vista della geografia culturale alcuni aspetti del pellegrinaggio a Santiago de Compostela, in Spagna, il capitolo prende in considerazione un testo letterario, il romanzo autobiografico "La ballata dei pellegrini" della scrittrice francese Edith De La Héronnière, pubblicato per la prima volta nel 1993 e tradotto in italiano nel 2004. Il romanzo racconta l’esperienza del pellegrinaggio giacobeo effettuato dall’autrice negli anni Novanta assieme a tre compagni di viaggio partendo da un cammino francese. In particolare, attraverso l’analisi di alcune parti del testo, si indagano le modalità attraverso le quali la narrazione costruisce e descrive lo spazio fisico e si…
Graph Clustering with Local Density-Cut
2018
In this paper, we introduce a new graph clustering algorithm, called Dcut. The basic idea is to envision the graph clustering as a local density-cut problem. To identify meaningful communities in a graph, a density-connected tree is first constructed in a local fashion. Building upon the local intuitive density-connected tree, Dcut allows partitioning a graph into multiple densely tight-knit clusters effectively and efficiently. We have demonstrated that our method has several attractive benefits: (a) Dcut provides an intuitive criterion to evaluate the goodness of a graph clustering in a more precise way; (b) Building upon the density-connected tree, Dcut allows identifying high-quality cl…
Canopy Architecture Appraisal by Fractal Dimension of 'Flordastar' Peach Trees Grafted onto Different Rootstocks
2007
The objective of this research was to evaluate the modification of canopy architecture of ''Flordastar'' peach (Prunus persica L. Batsch) grafted onto rootstocks with different vigour, by the use of fractal dimension (D). The hypothesis was that different vigour rootstocks are able to modify the complexity of the branching pattern and that this effect can be assessed by a geometric parameter such as the fractal dimension (D) of the 2D projection of tree branching structure. The observations were carried out in a four-year-old experimental orchard of cv. ''Flordastar'' peach trees grafted onto Ishtara, Barrier, GF677 and MrS 2/5 rootstocks. On digital pictures of leafless, dormant peach tree…
Global Upscaling of the MODIS Land Cover with Google Earth Engine and Landsat Data
2021
Image classification has become one of the most common applications in remote sensing yielding to the creation of a variety of operational thematic maps at multiple spatio-temporal scales. The information contained in these maps summarizes key characteristics related with the physical environment and provides fundamental information of the Earth for vegetation monitoring or land use status over time. However, high spatial resolution land cover maps are usually only produced for specific small regions or in an image tile. We present a general methodology to obtain a high spatial resolution land cover maps using Landsat spectral information, the powerful Google Earth Engine platform, and oper…
Learning to Rank Images for Complex Queries in Concept-based Search
2018
Concept-based image search is an emerging search paradigm that utilizes a set of concepts as intermediate semantic descriptors of images to bridge the semantic gap. Typically, a user query is rather complex and cannot be well described using a single concept. However, it is less effective to tackle such complex queries by simply aggregating the individual search results for the constituent concepts. In this paper, we propose to introduce the learning to rank techniques to concept-based image search for complex queries. With freely available social tagged images, we first build concept detectors by jointly leveraging the heterogeneous visual features. Then, to formulate the image relevance, …
Movie Script Similarity Using Multilayer Network Portrait Divergence
2020
International audience; This paper addresses the question of movie similarity through multilayer graph similarity measures. Recent work has shown how to construct multilayer networks using movie scripts, and how they capture different aspects of the stories. Based on this modeling, we propose to rely on the multilayer structure and compute different similarities, so we may compare movies, not from their visual content, summary, or actors, but actually from their own storyboard. We propose to do so using “portrait divergence”, which has been recently introduced to compute graph distances from summarizing graph characteristics. We illustrate our approach on the series of six Star Wars movies.
Global RDF Vector Space Embeddings
2017
Vector space embeddings have been shown to perform well when using RDF data in data mining and machine learning tasks. Existing approaches, such as RDF2Vec, use local information, i.e., they rely on local sequences generated for nodes in the RDF graph. For word embeddings, global techniques, such as GloVe, have been proposed as an alternative. In this paper, we show how the idea of global embeddings can be transferred to RDF embeddings, and show that the results are competitive with traditional local techniques like RDF2Vec.
Verification of linear hybrid systems with large discrete state spaces using counterexample-guided abstraction refinement
2017
Abstract We present a counterexample-guided abstraction refinement ( CEGAR) approach for the verification of safety properties of linear hybrid automata with large discrete state spaces, such as naturally arising when incorporating health state monitoring and degradation levels into the controller design. Such models can – in contrast to purely functional controller models – not be analyzed with hybrid verification engines relying on explicit representations of modes, but require fully symbolic representations for both the continuous and discrete part of the state space. The presented abstraction methods directly work on a symbolic representation of arbitrary non-convex combinations of line…
A study on graph representations for genetic programming
2020
Graph representations promise several desirable properties for Genetic Programming (GP); multiple-output programs, natural representations of code reuse and, in many cases, an innate mechanism for neutral drift. Each graph GP technique provides a program representation, genetic operators and overarching evolutionary algorithm. This makes it difficult to identify the individual causes of empirical differences, both between these methods and in comparison to traditional GP. In this work, we empirically study the behavior of Cartesian Genetic Programming (CGP), Linear Genetic Programming (LGP), Evolving Graphs by Graph Programming (EGGP) and traditional GP. By fixing some aspects of the config…