Search results for "ANNOTATION"
showing 10 items of 161 documents
Pini Language and PiniTree Ontology Editor: Annotation and Verbalisation for Atomised Journalism
2020
We present a new ontology language Pini and the PiniTree ontology editor supporting it. Despite Pini language bearing lot of similarities with RDF, UML class diagrams, Property Graphs and their frontends like Google Knowledge Graph and Protege, it is a more expressive language enabling FrameNet-style natural language annotation for Atomised journalism use case.
Grapevine and wine metabolomics-based guidelines for fair data and metadata management
2021
In the era of big and omics data, good organization, management, and description of experimental data are crucial for achieving high-quality datasets. This, in turn, is essential for the export of robust results, to publish reliable papers, make data more easily available, and unlock the huge potential of data reuse. Lately, more and more journals now require authors to share data and metadata according to the FAIR (Findable, Accessible, Interoperable, Reusable) principles. This work aims to provide a step-by-step guideline for the FAIR data and metadata management specific to grapevine and wine science. In detail, the guidelines include recommendations for the organization of data and meta…
CRISPR sequences are sometimes erroneously translated and can contaminate public databases with spurious proteins containing spaced repeats
2020
© The Author(s) 2020.
Semiautomatic Behavioral Change-Point Detection: A Case Study Analyzing Children Interactions With a Social Agent
2021
The study of human behaviors in cognitive sciences provides clues to understand and describe people’s personal and interpersonal functioning. In particular, the temporal analysis of behavioral dynamics can be a powerful tool to reveal events, correlations and causalities but also to discover abnormal behaviors. However, the annotation of these dynamics can be expensive in terms of temporal and human resources. To tackle this challenge, this paper proposes a methodology to semi-automatically annotate behavioral data. Behavioral dynamics can be expressed as sequences of simple dynamical processes: transitions between such processes are generally known as change-points. This paper describes th…
Perceptual Image Representations for Support Vector Machine Image Coding
2007
Support-vector-machine image coding relies on the ability of SVMs for function approximation. The size and the profile of the e-insensitivity zone of the support vector regressor (SVR) at some specific image representation determines (a) the amount of selected support vectors (the compression ratio), and (b) the nature of the introduced error (the compression distortion). However, the selection of an appropriate image representation is a key issue for a meaningful design of the e-insensitivity profile. For example, in image-coding applications, taking human perception into account is of paramount relevance to obtain a good rate-distortion performance. However, depending on the accuracy of t…
A novel Bayesian framework for relevance feedback in image content-based retrieval systems
2006
This paper presents a new algorithm for image retrieval in content-based image retrieval systems. The objective of these systems is to get the images which are as similar as possible to a user query from those contained in the global image database without using textual annotations attached to the images. The main problem in obtaining a robust and effective retrieval is the gap between the low level descriptors that can be automatically extracted from the images and the user intention. The algorithm proposed here to address this problem is based on the modeling of user preferences as a probability distribution on the image space. Following a Bayesian methodology, this distribution is the pr…
Automatic Image Annotation Using Random Projection in a Conceptual Space Induced from Data
2018
The main drawback of a detailed representation of visual content, whatever is its origin, is that significant features are very high dimensional. To keep the problem tractable while preserving the semantic content, a dimen- sionality reduction of the data is needed. We propose the Random Projection techniques to reduce the dimensionality. Even though this technique is sub-optimal with respect to Singular Value Decomposition its much lower computational cost make it more suitable for this problem and in par- ticular when computational resources are limited such as in mobile terminals. In this paper we present the use of a "conceptual" space, automatically induced from data, to perform automa…
Three-domain image representation for personal photo album management
2010
In this paper we present a novel approach for personal photo album management. Pictures are analyzed and described in three representation spaces, namely, faces, background and time of capture. Faces are automatically detected and rectified using a probabilistic feature extraction technique. Face representation is then produced by computing PCA (Principal Component Analysis). Backgrounds are represented with low-level visual features based on RGB histogram and Gabor filter bank. Temporal data is obtained through the extraction of EXIF (Exchangeable image file format) data. Each image in the collection is then automatically organized using a mean-shift clustering technique. While many system…
Image Recognition through Incremental Discriminative Common Vectors
2010
An incremental approach to the discriminative common vector (DCV) method for image recognition is presented. Two different but equivalent ways of computing both common vectors and corresponding subspace projections have been considered in the particular context in which new training data becomes available and learned subspaces may need continuous updating. The two algorithms are based on either scatter matrix eigendecomposition or difference subspace orthonormalization as with the original DCV method. The proposed incremental methods keep the same good properties than the original one but with a dramatic decrease in computational burden when used in this kind of dynamic scenario. Extensive …
ChiLab4It system in the QA4FAQ competition
2017
ChiLab4It is the Question Answering system (QA) for Frequently Asked Questions (FAQ) developed by the Computer-Human Interaction Laboratory (ChiLab) at the University of Palermo for participating to the QA4FAQ task at EVALITA 2016 competition. The system is the versioning of the QuASIt framework developed by the same authors, which has been customized to address the particular task. This technical report describes the strategies that have been imported from QuASIt for implementing ChiLab4It, the actual system implementation, and the comparative evaluations with the results of the other participant tools, as provided by the organizers of the task. ChiLab4It was the only system whose score re…