Search results for "pattern recognition"
showing 10 items of 2301 documents
Remote sensing image segmentation by active queries
2012
Active learning deals with developing methods that select examples that may express data characteristics in a compact way. For remote sensing image segmentation, the selected samples are the most informative pixels in the image so that classifiers trained with reduced active datasets become faster and more robust. Strategies for intelligent sampling have been proposed with model-based heuristics aiming at the search of the most informative pixels to optimize model's performance. Unlike standard methods that concentrate on model optimization, here we propose a method inspired in the cluster assumption that holds in most of the remote sensing data. Starting from a complete hierarchical descri…
Discovering single classes in remote sensing images with active learning
2012
When dealing with supervised target detection, the acquisition of labeled samples is one of the most critical phases: the samples must be yet representative of the class of interest, but must also be found among a vast majority of non-target examples. Moreover, the efficiency of the search is also an issue, since the samples labeled as background are not used by target detectors such as the support vector data description (SVDD). In this work we propose a competitive and effective approach to identify the most relevant training samples for one-class classification based on the use of an active learning strategy. The SVDD classifier is first trained with insufficient target examples. It is t…
Specific transfer effects following variable priority dual-task training in older adults
2016
International audience; Purpose: Past divided attention training studies in older adults have suggested that variable priority training (VPT) tends to show larger improvement than fixed priority training (FPT). However, it remains unclear whether VPT leads to larger transfer effects. Methods: In this study, eighty-three older adults aged between 55 and 65 received five 1-hour sessions of VPT, FPT or of an active placebo. VPT and FPT subjects trained on a complex dual-task condition with variable stimulus timings in order to promote more flexible and self-guided strategies with regard to attentional priority devoted to the concurrent tasks. Real-time individualized feedback was provided to e…
An architecture for autonomous agents exploiting conceptual representations
1998
An architecture for autonomous agents is proposed that integrates the functional and the behavioral approaches to robotics. The integration is based on the introduction of a conceptual level, linking together a subconceptual, behavioral, level, and a linguistic level, encompassing symbolic representation and data processing. The proposed architecture is described with reference to an experimental setup, in which the robot task is that of building a significant description of its working environment. © 1998 Elsevier Science B.V. All rights reserved.
A context-aware approach for long-term behavioural change detection and abnormality prediction in ambient assisted living
2015
This research aims to describe pattern recognition models for detecting behavioural and health-related changes in a patient who is monitored continuously in an assisted living environment. The early anticipation of anomalies can improve the rate of disease prevention. Here we present different learning techniques for predicting abnormalities and behavioural trends in various user contexts. In this paper we described a Hidden Markov Model based approach for detecting abnormalities in daily activities, a process of identifying irregularity in routine behaviours from statistical histories and an exponential smoothing technique to predict future changes in various vital signs. The outcomes of t…
ActRec: A Wi-Fi-Based Human Activity Recognition System
2020
In this paper, we develop a Wi-Fi-based activity recognition system called ActRec, which can be used for the remote monitoring of elderly. ActRec comprises two parts: radio-frequency (RF) sensing and machine learning. In the RF sensing part, two laptops act as transmitter and receiver to record the channel transfer function of an indoor environment. This RF data is collected in the presence of seven human participants performing three activities: walking, falling, and sitting. The RF data containing the fingerprints of user activity is then pre-processed with various signal processing algorithms to reduce noise effects and to estimate the mean Doppler shift (MDS) of each data sample. We pro…
Adaptive Bias Field Correction: Application on Abdominal MR Images
2017
Segmentation of medical images is one of the most important phases for disease diagnosis. Accuracy, robustness and stability of the results obtained by image segmentation is a major concern. Many segmentation methods rely on absolute values of intensity level, which are affected by a bias term due to in-homogeneous field in magnetic resonance images. The main objective of this paper is two folded: (1) To show efficiency of an energy minimization based approach, which uses intrinsic component optimization, on abdominal magnetic resonance images. (2) To propose an adaptive method to stop the optimization automatically. The proposed method can control the value of the energy functional and sto…
Data-based modeling of vehicle crash using adaptive neural-fuzzy inference system
2014
Vehicle crashes are considered to be events that are extremely complex to be analyzed from the mathematical point of view. In order to establish a mathematical model of a vehicle crash, one needs to consider various areas of research. For this reason, to simplify the analysis and improve the modeling process, in this paper, a novel adaptive neurofuzzy inference system (ANFIS-based) approach to reconstruct kinematics of colliding vehicles is presented. A typical five-layered ANFIS structure is trained to reproduce kinematics (acceleration, velocity, and displacement) of a vehicle involved in an oblique barrier collision. Subsequently, the same ANFIS structure is applied to simulate different…
Assessing the Relationship Between Attitudinal and Perceptual Component of Body Image Disturbance Using Virtual Reality
2018
Body image disturbance (BID) affects quality of life even in the absence of clinically diagnosable eating pathology, and numerous studies have shown its crucial role in the emergence and maintenance of eating disorders. This study aimed at exploring attitudinal and perceptual components of BID using a novel virtual reality (VR)-based paradigm. A community sample of women (N = 27) recreated in VR their perceived body in both an allocentric (third-person view) and egocentric (first-person view) perspective. Specifically, women were able to choose between a wide range of three-dimensional bodies spanning body mass index 12.5-42.5 kg/m2. Attitudinal indexes of BID (body dissatisfaction, body un…
Cerebellar patients demonstrate preserved implicit knowledge of association strengths in musical sequences
2006
Recent findings suggest the involvement of the cerebellum in perceptual and cognitive tasks. Our study investigated whether cerebellar patients show musical priming based on implicit knowledge of tonal-harmonic music. Participants performed speeded phoneme identification on sung target chords, which were either related or less-related to prime contexts in terms of the tonal-harmonic system. As groups, both cerebellar patients and age-matched controls showed facilitated processing for related targets, as previously observed for healthy young adults. The outcome suggests that an intact cerebellum is not mandatory for accessing implicit knowledge stored in long-term memory and for its influenc…