Search results for " Filtering"
showing 10 items of 108 documents
Biologically Inspired Model for Inference of 3D Shape from Texture.
2015
A biologically inspired model architecture for inferring 3D shape from texture is proposed. The model is hierarchically organized into modules roughly corresponding to visual cortical areas in the ventral stream. Initial orientation selective filtering decomposes the input into low-level orientation and spatial frequency representations. Grouping of spatially anisotropic orientation responses builds sketch-like representations of surface shape. Gradients in orientation fields and subsequent integration infers local surface geometry and globally consistent 3D depth. From the distributions in orientation responses summed in frequency, an estimate of the tilt and slant of the local surface can…
Reinforced Room-Temperature Spin Filtering in Chiral Paramagnetic Metallopeptides
2020
Chirality-induced spin selectivity (CISS), whereby helical molecules polarize the spin of electrical current, is an intriguing effect with potential applications in nanospintronics. In this nascent field, the study of the CISS effect using paramagnetic chiral molecules, which could introduce another degree of freedom in controlling the spin transport, remains so far unexplored. To address this challenge, herein we propose the use of self-assembled monolayers (SAMs) of helical lanthanide-binding peptides. To elucidate the effect of the paramagnetic nuclei, monolayers of the peptide coordinating paramagnetic or diamagnetic ions are prepared. By means of spin-dependent electrochemistry, the CI…
LeSSS: Learned Shared Semantic Spaces for Relating Multi-Modal Representations of 3D Shapes
2015
In this paper, we propose a new method for structuring multi-modal representations of shapes according to semantic relations. We learn a metric that links semantically similar objects represented in different modalities. First, 3D-shapes are associated with textual labels by learning how textual attributes are related to the observed geometry. Correlations between similar labels are captured by simultaneously embedding labels and shape descriptors into a common latent space in which an inner product corresponds to similarity. The mapping is learned robustly by optimizing a rank-based loss function under a sparseness prior for the spectrum of the matrix of all classifiers. Second, we extend …
VIGIL System: A Computer Vision-Based AID System. Evaluation in a Ring Motorway Section in Madrid
1994
Abstract The VIGIL system is an Automatic Incident and Congestion Detection System based on computer vision technology tor motorway applications. VIGIL is constituted by two main modules, the Local Sensor Module and the Central System module. The objective of this paper is to describe the VIGIL Central System functions, mainly the alarm filtering and management capabilities, and to present the field trial currently carried out in Madrid within the ARTIS project (Advanced RTI in Spain) supported by the Tranport Telematic Programme of the EC.
AN ONTOLOGY-BASED APPROACH TO PROVIDE PERSONNALIZED RECOMMENDATIONS USING A STOCHASTIC ALGORITHM
2011
International audience; The use of personalized recommender systems to assist users in the selection of products is becoming more and more popular and wide-spread. The purpose of a recommender system is to provide the most suitable items from an knowledge base, according the user knowledge, tastes, interests, ... These items are generally proposed as ordered lists. In this article, we propose to combine works from adaptive hypermedia systems, semantic web and combinatory to create a new kind of recommender systems suggesting combinations of items corresponding to the user.
Designing ‘trait-based null model’ approaches to investigate community assembly mechanisms
2014
SPEEAECOLDURGEAPSIéquipe CAPA; During the last decade, many studies have addressed the signature of community assembly processes by assessing the deviation of a functional diversity pattern from that expected in null communities, using a randomization algorithm. The basic principle has been to compare the functional structure of a ‘local community’ with a set of randomly generated communities from a ‘regional species pool’. Specifically, it allows assessing the extent to which species constituting a community are functionally more or less similar than expected under the assumption of a random assembly, thus revealing the influence of assembly processes such as competition or environmental a…
Observateur et contrôle optimal : améliorer l'efficacité de la conduite automobile avec Kalman et Pontryagin
2010
The PhD presents a combined approach to improving individual car efficiency. An optimal observer, the Extended Kalman Filter, is used to create an efficiency model for the car. Particular attention was paid to handling the asynchronous and redundant nature of the measurement data. A low-cost sensor suite developed to measure data is described. This sensor suite was installed on multiple vehicles to good success. It employsan accelerometer, gps, fuel injector timer, and Vss input to measure all the data necessary to reconstruct the car's state. This observer and sensor suite can be used as the base for any study which requires car efficiency maps, allowing research to proceed without manufac…
Comparing ranking-based collaborative filtering algorithms to a rating-based alternative in recommender systems context
2017
Suuri sisältövalikoima eri internet palveluissa, kuten verkkokaupoissa, voi aiheuttaa liian suurta informaatiomäärää, mikä heikentää asiakaskokemusta. Suosittelujärjestelmät ovat teknologioita, jotka tukevat asiakkaan päätöksentekoa tarjoamalla ennustettuja suosituksia. On yleistä, että asiakkaalle näytetään lista tuotteista, joista asiakas voisi pitää, esimerkiksi top-10 lista elokuvista. Perinteisesti nämä listat ovat tuotettu käyttäen perinteistä arvosanapohjaista menetelmää, missä tuntemattomille tuotteille ennustetaan arvosana ja järjestetty lista muodostetaan arvosanojen perusteella. Sijoitusperusteinen lähestyminen laskee käyttäjien väliset samankaltaisuudet ja ennustaa järjestetyn l…
Less Data Same Information for Event-Based Sensors: A Bioinspired Filtering and Data Reduction Algorithm
2018
Sensors provide data which need to be processed after acquisition to remove noise and extract relevant information. When the sensor is a network node and acquired data are to be transmitted to other nodes (e.g., through Ethernet), the amount of generated data from multiple nodes can overload the communication channel. The reduction of generated data implies the possibility of lower hardware requirements and less power consumption for the hardware devices. This work proposes a filtering algorithm (LDSI&mdash
A Sentiment Enhanced Deep Collaborative Filtering Recommender System
2021
Recommender systems use advanced analytic and learning techniques to select relevant information from massive data and inform users’ smart decision-making on their daily needs. Numerous works exploiting user’s sentiments on products to enhance recommendations have been introduced. However, there has been relatively less work exploring higher-order user-item features interactions for sentiment enhanced recommender system. In this paper, a novel Sentiment Enhanced Deep Collaborative Filtering Recommender System (SE-DCF) is developed. The architecture is based on a Neural Attention network component aggregated with the output predictions of a Convolution Neural Network (CNN) recommender. Speci…