Search results for "artificial intelligence"
showing 10 items of 6122 documents
Automatic orientation and 3D modelling from markerless rock art imagery
2013
This paper investigates the use of two detectors and descriptors on image pyramids for automatic image orientation and generation of 3D models. The detectors and descriptors replace manual measurements and are used to detect, extract and match features across multiple imagery. The Scale-Invariant Feature Transform (SIFT) and the Speeded Up Robust Features (SURF) will be assessed based on speed, number of features, matched features, and precision in image and object space depending on the adopted hierarchical matching scheme. The influence of applying in addition Area Based Matching (ABM) with normalised cross-correlation (NCC) and least squares matching (LSM) is also investigated. The pipel…
In vivo evaluation of three-dimensional of volumetric changes using a CAD/CAM chair-side system : technical procedure
2017
An intraoral digital scanner in combination with specialized three-dimensional surface analysis software monitors volumetric changes to soft tissues or dental restorations. This technology can evaluate the success of a specific technique or medium- or long-term clinical outcomes in both clinical and research situations. This article describes how this technology was used to provide immediate chair-side data analysis without the help of specialized laboratory support. Key words:Intraoral scanner, CAD-CAM, best fit-method, surface tessellation language.
Analysis and Comparison of Deep Learning Networks for Supporting Sentiment Mining in Text Corpora
2020
In this paper, we tackle the problem of the irony and sarcasm detection for the Italian language to contribute to the enrichment of the sentiment analysis field. We analyze and compare five deep-learning systems. Results show the high suitability of such systems to face the problem by achieving 93% of F1-Score in the best case. Furthermore, we briefly analyze the model architectures in order to choose the best compromise between performances and complexity.
Automatic Dictionary Creation by Sub-symbolic Encoding of Words
2006
This paper describes a technique for automatic creation of dictionaries using sub-symbolic representation of words in cross-language context. Semantic relationship among words of two languages is extracted from aligned bilingual text corpora. This feature is obtained applying the Latent Semantic Analysis technique to the matrices representing terms co-occurrences in aligned text fragments. The technique allows to find the “best translation” according to a properly defined geometric distance in an automatically created semantic space. Experiments show an interesting correctness of 95% obtained in the best case.
Review of Non-English Corpora Annotated for Emotion Classification in Text
2020
In this paper we try to systematize the information about the available corpora for emotion classification in text for languages other than English with the goal to find what approaches could be used for low-resource languages with close to no existing works in the field. We analyze the corresponding volume, emotion classification schema, language of each corresponding corpus and methods employed for data preparation and annotation automation. We’ve systematized twenty-four papers representing the corpora and found that corpora were mostly for the most spoken world languages: Hindi, Chinese, Turkish, Arabic, Japanese etc. A typical corpus contained several thousand of manually-annotated ent…
A Methodology for Bilingual Lexicon Extraction from Comparable Corpora
2015
Dictionary extraction using parallel corpora is well established. However, for many language pairs parallel corpora are a scarce resource which is why in the current work we discuss methods for dictionary extraction from comparable corpora. Hereby the aim is to push the boundaries of current approaches, which typically utilize correlations between co-occurrence patterns across languages, in several ways: 1) Eliminating the need for initial lexicons by using a bootstrapping approach which only requires a few seed translations. 2) Implementing a new approach which first establishes alignments between comparable documents across languages, and then computes cross-lingual alignments between wor…
Graph-based exploration and clustering analysis of semantic spaces
2019
Abstract The goal of this study is to demonstrate how network science and graph theory tools and concepts can be effectively used for exploring and comparing semantic spaces of word embeddings and lexical databases. Specifically, we construct semantic networks based on word2vec representation of words, which is “learnt” from large text corpora (Google news, Amazon reviews), and “human built” word networks derived from the well-known lexical databases: WordNet and Moby Thesaurus. We compare “global” (e.g., degrees, distances, clustering coefficients) and “local” (e.g., most central nodes and community-type dense clusters) characteristics of considered networks. Our observations suggest that …
Supporting Emotion Automatic Detection and Analysis over Real-Life Text Corpora via Deep Learning: Model, Methodology, and Framework
2021
This paper describes an approach for supporting automatic satire detection through effective deep learning (DL) architecture that has been shown to be useful for addressing sarcasm/irony detection problems. We both trained and tested the system exploiting articles derived from two important satiric blogs, Lercio and IlFattoQuotidiano, and significant Italian newspapers.
The computation of word associations
2002
It is shown that basic language processes such as the production of free word associations and the generation of synonyms can be simulated using statistical models that analyze the distribution of words in large text corpora. According to the law of association by contiguity, the acquisition of word associations can be explained by Hebbian learning. The free word associations as produced by subjects on presentation of single stimulus words can thus be predicted by applying first-order statistics to the frequencies of word co-occurrences as observed in texts. The generation of synonyms can also be conducted on co-occurrence data but requires second-order statistics. The reason is that synony…
Revisiting corpus creation and analysis tools for translation tasks
2016
Many translation scholars have proposed the use of corpora to allow professional translators to produce high quality texts which read like originals. Yet, the diffusion of this methodology has been modest, one reason being the fact that software for corpora analyses have been developed with the linguist in mind, which means that they are generally complex and cumbersome, offering many advanced features, but lacking the level of usability and the specific features that meet translators’ needs. To overcome this shortcoming, we have developed TranslatorBank, a free corpus creation and analysis tool designed for translation tasks. TranslatorBank supports the creation of specialized monolingual …