Search results for "artificial intelligence"
showing 10 items of 6122 documents
Using the fibre structure of paper to determine authenticity of the documents: analysis of transmitted light images of stamps and banknotes.
2014
A novel method is presented for distinguishing postal stamp forgeries and counterfeit banknotes from genuine samples. The method is based on analyzing differences in paper fibre networks. The main tool is a curvelet-based algorithm for measuring overall fibre orientation distribution and quantifying anisotropy. Using a couple of more appropriate parameters makes it possible to distinguish forgeries from genuine originals as concentrated point clouds in two- or three-dimensional parameter space.
Semi-supervised Hyperspectral Image Classification with Graphs
2006
This paper presents a semi-supervised graph-based method for the classification of hyperspectral images. The method is designed to exploit the spatial/contextual information in the im- ages through composite kernels. The proposed method produces smoother classifications with respect to the intrinsic structure collectively revealed by known labeled and unlabeled points. Good accuracy in high dimensional spaces and low number of labeled samples (ill-posed situations) are produced as compared to standard inductive support vector machines.
Including invariances in SVM remote sensing image classification
2012
This paper introduces a simple method to include invariances in support vector machine (SVM) for remote sensing image classification. We rely on the concept of virtual support vectors, by which the SVM is trained with both the selected support vectors and synthetic examples encoding the invariance of interest. The algorithm is very simple and effective, as demonstrated in two particularly interesting examples: invariance to the presence of shadows and to rotations in patchbased image segmentation. The improved accuracy (around +6% both in OA and Cohen's κ statistic), along with the simplicity of the approach encourage its use and extension to encode other invariances and other remote sensin…
Comparing fMRI inter-subject correlations between groups using permutation tests
2018
AbstractInter-subject correlation (ISC) based analysis is a conceptually simple approach to analyze functional magnetic resonance imaging (fMRI) data acquired under naturalistic stimuli such as a movie. We describe and validate the statistical approaches for comparing ISCs between two groups of subjects implemented in the ISC toolbox, which is an open source software package for ISC-based analysis of fMRI data. The approaches are based on permutation tests. We validated the approaches using five different data sets from the ICBM functional reference battery tasks. First, we created five null datasets (one for each task) by dividing the subjects into two matched groups and assumed that no gr…
On the category Set(JCPos)
2006
Category Set(JCPos) of lattice-valued subsets of sets is introduced and studied. We prove that it is topological over SetxJCPos and show its ''natural'' coalgebraic subcategory.
The influence of task-irrelevant music on language processing: syntactic and semantic structures.
2011
Recent research has suggested that music and language processing share neural resources, leading to new hypotheses about interference in the simultaneous processing of these two structures. The present study investigated the effect of a musical chord's tonal function on syntactic processing (Experiment 1) and semantic processing (Experiment 2) using a cross-modal paradigm and controlling for acoustic differences. Participants read sentences and performed a lexical decision task on the last word, which was, syntactically or semantically, expected or unexpected. The simultaneously presented (task-irrelevant) musical sequences ended on either an expected tonic or a less-expected subdominant ch…
In praise of artifice reloaded: Caution with natural image databases in modeling vision
2019
Subjective image quality databases are a major source of raw data on how the visual system works in naturalistic environments. These databases describe the sensitivity of many observers to a wide range of distortions of different nature and intensity seen on top of a variety of natural images. Data of this kind seems to open a number of possibilities for the vision scientist to check the models in realistic scenarios. However, while these natural databases are great benchmarks for models developed in some other way (e.g., by using the well-controlled artificial stimuli of traditional psychophysics), they should be carefully used when trying to fit vision models. Given the high dimensionalit…
Visualization in comparative music research
2007
Computational analysis of large musical corpora provides an approach that overcomes some of the limitations of manual analysis related to small sample sizes and subjectivity. The present paper aims to provide an overview of the computational approach to music research. It discusses the issues of music representation, musical feature extraction, digital music collections, and data mining techniques. Moreover, it provides examples of visualization of large musical collections.
From the many voices to the subject positions in anti-globalization discourse: Enunciative pragmatics and the polyphonic organization of subjectivity
2011
This contribution presents enunciative pragmatics as a methodological orientation to account for how written texts are contextualized in the act of reading. As an offspring of the pragmatic turn among French-speaking linguists, the enunciative approach is mobilized to analyze the cover page of a cartoon on the anti-globalization legend Jose Bove. Focusing on the complex interpretive problems of political discourse, the enunciative-pragmatic approach shows how readers construct subject positions following the text's complex indexicality. It reveals the polyphonic play of voices orchestrated by the enunciative markers. Therefore, enunciative pragmatics promises to bridge the gulf that separat…
Mini-drones swarms and their potential in conflict situations
2021
Drones are currently used for a wide range of operations, such as border surveillance, general surveillance, reconnaissance, transport, aerial photography, traffic control, earth observation, communications, broadcasting, and armed attacks. This paper examines the swarming and associated abilities to overwhelm a combatant as well as bring extra functionality by means of extra sensors spread throughout the swarm. The strategy of stealth is becoming increasingly less effective. Combatants can not only sense them, but can also successfully destroy them (although this cannot be said for nano-drones). For mini-drones, objectives can be enhanced by the strategy of overwhelming. peerReviewed