Search results for "InformationSystems_INFORMATIONSTORAGEANDRETRIEVAL"
showing 3 items of 53 documents
SIFT Texture Description for Understanding Breast Ultrasound Images
2014
Texture is a powerful cue for describing structures that show a high degree of similarity in their image intensity patterns. This paper describes the use of Self-Invariant Feature Transform (SIFT), both as low-level and high-level descriptors, applied to differentiate the tissues present in breast US images. For the low-level texture descriptors case, SIFT descriptors are extracted from a regular grid. The high-level texture descriptor is build as a Bag-of-Features (BoF) of SIFT descriptors. Experimental results are provided showing the validity of the proposed approach for describing the tissues in breast US images.
Neuropsychological Alterations in Children Affected by Obstructive Sleep Apnea Syndrome
2020
Sleep-related breathing disorders are a group of clinical conditions ranging from habitual snoring to obstructive sleep apnea syndrome (OSAS) during the lifespan. In children, other risk factors are represented by adenotonsillar hypertrophy, rhinitis, nasal structure alteration, cleft palate, velopharyngeal flap surgery, pharyngeal masses, craniofacial malformations, genetic syndrome (i.e. Down syndrome, Crouzon syndrome, and Apert syndrome), genetic hypoplasia mandibular (i.e. Pierre Robin syndrome, Treacher Collins syndrome, Shy-Drager syndrome, and Cornelia De Lange syndrome), craniofacial traumas, chronic or seasonal rhinitis, asthma, neuromuscular syndromes, brainstem pathologies (i.e.…
User session level diverse reranking of search results
2018
Most Web search diversity approaches can be categorized as Document Level Diversification (DocLD), Topic Level Diversification (TopicLD) or Term Level Diversification (TermLD). DocLD selects the relevant documents with minimal content overlap to each other. It does not take the coverage of query subtopics into account. TopicLD solves this by modeling query subtopics explicitly. However, the automatic mining of query subtopics is difficult. TermLD tries to cover as many query topic terms as possible, which reduces the task of finding a query's subtopics into finding a set of representative topic terms. In this paper, we propose a novel User Session Level Diversification (UserLD) approach bas…