Search results for "Trie"
showing 10 items of 4468 documents
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…
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…
Classification Similarity Learning Using Feature-Based and Distance-Based Representations: A Comparative Study
2015
Automatically measuring the similarity between a pair of objects is a common and important task in the machine learning and pattern recognition fields. Being an object of study for decades, it has lately received an increasing interest from the scientific community. Usually, the proposed solutions have used either a feature-based or a distance-based representation to perform learning and classification tasks. This article presents the results of a comparative experimental study between these two approaches for computing similarity scores using a classification-based method. In particular, we use the Support Vector Machine as a flexible combiner both for a high dimensional feature space and …
An improved distance-based relevance feedback strategy for image retrieval
2013
Most CBIR (content based image retrieval) systems use relevance feedback as a mechanism to improve retrieval results. NN (nearest neighbor) approaches provide an efficient method to compute relevance scores, by using estimated densities of relevant and non-relevant samples in a particular feature space. In this paper, particularities of the CBIR problem are exploited to propose an improved relevance feedback algorithm based on the NN approach. The resulting method has been tested in a number of different situations and compared to the standard NN approach and other existing relevance feedback mechanisms. Experimental results evidence significant improvements in most cases.
Interactive Image Retrieval Using Smoothed Nearest Neighbor Estimates
2010
Relevance feedback has been adopted by most recent Content Based Image Retrieval systems to reduce the semantic gap that exists between the subjective similarity among images and the similarity measures computed in a given feature space. Distance-based relevance feedback using nearest neighbors has been recently presented as a good tradeoff between simplicity and performance. In this paper, we analyse some shortages of this technique and propose alternatives that help improving the efficiency of the method in terms of the retrieval precision achieved. The resulting method has been evaluated on several repositories which use different feature sets. The results have been compared to those obt…
Geometric Algebra Rotors for Sub-symbolic Coding of Natural Language Sentences
2007
A sub-symbolic encoding methodology for natural language sentences is presented. The procedure is based on the creation of an LSA-inspired semantic space and associates rotation operators derived from Geometric Algebra to word bigrams of the sentence. The operators are subsequently applied to an orthonormal standard basis of the created semantic space according to the order in which words appear in the sentence. The final rotated basis is then coded as a vector and its orthogonal part constitutes the sub-symbolic coding of the sentence. Preliminary experimental results for a classification task, compared with the traditional LSA methodology, show the effectiveness of the approach.
Interferometric measurement of complex-field changes in transient detection imaging.
2020
We report an experimental method that combines nonlinear-crystal-based transient detection imaging (TDI) with interferometric complex-field retrieval. The system allows measuring both phase and amplitude of a dynamic scene while suppressing stationary background. Theoretical and experimental results prove the linear relation existing between input and output phases, as well as the benefits of phase analysis for both detection and measurement with high resolutions of λ/30, even under noisy conditions. Additionally, we present experimental evidence of the remarkable ability of the technique to detect phase sign changes in the scene —what we call differential-phase TDI— showing great detection…
Research opportunities in performance measurement in public utilities regulation
2015
Purpose – The purpose of this paper is to propose a method to choose a set of scientific articles about performance measurement in public utilities regulation. The method is designed to identify references with high academic relevance in databases accessed via the internet, and, through these articles, to perform a mapping of these publications and conduct a systemic analysis. Design/methodology/approach – The study is characterized as exploratory and descriptive with a qualitative and quantitative approach. Incorporates an inductive logic, and draws on primary and secondary data sources. The research involves the application of a technical procedure for selection and study of selected art…
Revealing the unique features of each individual’s muscle activation signatures
2020
AbstractThere is growing evidence that each individual has unique movement patterns, or signatures. The exact origin of these movement signatures however, remains unknown. We developed an approach that can identify individual muscle activation signatures during two locomotor tasks (walking and pedalling). A linear Support Vector Machine was used to classify 78 participants based on their electromyographic (EMG) patterns measured on eight lower limb muscles. To provide insight into decision making by the machine learning classification model, a Layer-wise Relevance Propagation (LRP) approach was implemented. This enabled the model predictions to be decomposed into relevance scores for each i…
Multiperspective Evaluation of Reference Models – Towards a Framework
2003
Within the information systems field, reference models have been known for many years. Despite the relevance of reference model quality, little research has been done on their systematic evaluation. Based on an analysis of prior work on reference model quality, we propose a framework for the multiperspective evaluation of reference models. The framework comprises 15 perspectives. Each perspective is discussed with respect to its strengths and limitations. As well, we provide examples of the types of research that have already been undertaken on each perspective.