2,836 research outputs found
Transferencia de técnicas de aprendizaje y mejora del rendimiento en la segmentación semántica profunda de nubes de puntos del patrimonio construido
No full text[EN] The growing availability of three-dimensional (3D) data, such as point clouds, coming from Light Detection and Ranging (LiDAR), Mobile Mapping Systems (MMSs) or Unmanned Aerial Vehicles (UAVs), provides the opportunity to rapidly generate 3D models to support the restoration, conservation, and safeguarding activities of cultural heritage (CH). The so-called scan-to-BIM process can, in fact, benefit from such data, and they can themselves be a source for further analyses or activities on the archaeological and built heritage. There are several ways to exploit this type of data, such as Historic Building Information Modelling (HBIM), mesh creation, rasterisation, classification, and semantic segmentation. The latter, referring to point clouds, is a trending topic not only in the CH domain but also in other fields like autonomous navigation, medicine or retail. Precisely in these sectors, the task of semantic segmentation has been mainly exploited and developed with artificial intelligence techniques. In particular, machine learning (ML) algorithms, and their deep learning (DL) subset, are increasingly applied and have established a solid state-of-the-art in the last half-decade. However, applications of DL techniques on heritage point clouds are still scarce; therefore, we propose to tackle this framework within the built heritage field. Starting from some previous tests with the Dynamic Graph Convolutional Neural Network (DGCNN), in this contribution close attention is paid to: i) the investigation of fine-tuned models, used as a transfer learning technique, ii) the combination of external classifiers, such as Random Forest (RF), with the artificial neural network, and iii) the evaluation of the data augmentation results for the domain-specific ArCH dataset. Finally, after taking into account the main advantages and criticalities, considerations are made on the possibility to profit by this methodology also for non-programming or domain experts.[ES] La creciente disponibilidad de datos tridimensionales (3D), como nubes de puntos, provenientes de la detección de la luz y distancia (LiDAR), sistemas de mapeado móvil (MMS) o vehículos aéreos no tripulados (UAV), brinda la oportunidad de generar rápidamente modelos 3D para apoyar las actividades de restauración, conservación y salvaguardia del patrimonio cultural (CH). El llamado proceso de escaneado-a-BIM puede, de hecho, beneficiarse de dichos datos, y ellos mismos pueden ser una fuente para futuros análisis o actividades sobre el patrimonio arqueológico y el construido. Hay varias formas de explotar este tipo de datos, como el modelado de información de edificios históricos (HBIM), la creación de mallas, la rasterización, la clasificación y la segmentación semántica. Este último, referido a las nubes de puntos, es un tema de máxima actualidad no solo en el dominio del PC sino también en otros campos como la navegación autónoma, la medicina o el comercio minorista. Precisamente en estos sectores, la tarea de la segmentación semántica se ha explotado y desarrollado principalmente con técnicas de inteligencia artificial. En particular, los algoritmos de aprendizaje automático (AA) y su subconjunto de aprendizaje profundo (AP) se aplican cada vez más y han establecido un sólido estado de la técnica en la última media década. Sin embargo, las aplicaciones de las técnicas de AP en las nubes de puntos tradicionales son todavía escasas; por tanto, nos proponemos abordar este marco dentro del ámbito del patrimonio construido. Partiendo de algunas pruebas anteriores con la Red Neural Convolucional de Gráfico Dinámico (DGCNN), en esta contribución se presta atención a: i) la investigación de modelos afinados, utilizados como técnica de aprendizaje por transferencia, ii) la combinación de clasificadores externos, como Random Forest (RF), con la red neuronal artificial, y iii) la evaluación de los resultados de aumentación de datos para el conjunto de datos específico del dominio ArCH. Finalmente, después de tener en cuenta las principales ventajas y criticidades, se hace una consideración sobre la posibilidad de beneficiarse de esta metodología también a expertos no programadores o del campo.Matrone, F.; Martini, M. (2021). Transfer learning and performance enhancement techniques for deep semantic segmentation of built heritage point clouds. Virtual Archaeology Review. 12(25):73-84. https://doi.org/10.4995/var.2021.15318OJS73841225Armeni, I., Sener, O., Zamir, A. 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Identità regionale e identità nazionale: un'analisi comparata.
No full textVengono analizzati i due concetti sotto una prospettiva sociopsicologica principalmente sulla base della Teoria dell'Identità Sociale e dei rapporti intergruppi. Sono riportate le diverse concezioni dei processi identificatori delimitandone i confini attraverso le varie definizioni. Inoltre, vengono prese in considerazione le tecniche di misurazione nei diversi approcci. Infine, vengono formulate alcune considerazioni relative ai problemi (politici) derivanti dal forte legame esistente fra territorio e identità
Deprivazione relativa e identità sociale
No full textIn questo lavoro vengono analizzate le relazioni esistenti tra il Modello della deprivazione relativa e la Teoria dell'identità sociale. Nella prima parte sono presentate le diverse definizioni del concetto di deprivazione relativa e le varie tipologie del costrutto. Nella seconda parte viene esaminato il legame teorico ed empirico fra questo modello e i processi di identificazione sociale
Identità regionale
No full textVengono analizzati i processi di identità regionale: in questo caso "regione" si riferisce non solo ad un determinato spazio geografico o politico, quanto piuttosto ad un gruppo che vive e condivide uno specifico ambiente socioculturale. L' identificazione con la regione consiste in un processo di autocategorizzazione in cui un individuo considera come proprie quelle caratteristiche che stereotipicamente distinguono il cittadino della sua regione da un altro
Identità sociale, media e gruppi
No full textLa sezione monografica del fascicolo è composta dalla presentazione del curatore e da sei contributi.
Il primo articolo affronta l'analisi dell'attività di newsmaking di quotidiani locali su un tema ambientale. I due lavori successivi focalizzano la loro attenzione sul mondo web. In altri due articoli vengono esaminate tematiche applicate ai contesti organizzativi. L'ultimo contributo, infine, si occupa della tecnica del focus group
Dimensioni dell'identità sociale
No full textNel volume vengono analizzate e comparate le forme dell'identità regionale e nazionale, e le relative tecniche di misurazione. Segue poi l'esame delle relazioni esistenti tra il Modello della deprivazione relativa e la Teoria dell'identità sociale. Viene trattato, inoltre, il tema che riguarda l'identità sociale e la comunicazione in rete e, in particolare, il ruolo rilevante della comunicazione mediata dal computer. Infine, viene presentata una ricerca empirica nella quale sono prese in considerazione la Teoria dell'identità sociale e quella della deprivazione relativa come strumenti per la comprensione delle strategie comportamentali
Edgar Martini per Engelbert Drerup: un ritratto dimenticato
No full textA biographical sketch of Engelbert Drerup written by Edgar Martini on the occasion of Drerup’s 60th birthday. The text was originally published in 1931, in the Catholic journal «Der Wächter». It is reprinted here with an introduction, notes and an Italian translation.Viene ripubblicato un dimenticato profilo biografico e critico del filologo Engelbert Drerup scritto dal collega e amico Edgar Martini, originariamente apparso nel 1931 nel periodico cattolico «Der Wächter». Il testo è presentato criticamente e accompagnato da una traduzione italiana e da note di commento
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