Search results for "Pattern recognition"
showing 10 items of 2301 documents
2021
Abstract Reliable patient-specific ventricular repolarization times (RTs) can identify regions of functional block or afterdepolarizations, indicating arrhythmogenic cardiac tissue and the risk of sudden cardiac death. Unipolar electrograms (UEs) record electric potentials, and the Wyatt method has been shown to be accurate for estimating RT from a UE. High-pass filtering is an important step in processing UEs, however, it is known to distort the T-wave phase of the UE, which may compromise the accuracy of the Wyatt method. The aim of this study was to examine the effects of high-pass filtering, and improve RT estimates derived from filtered UEs. We first generated a comprehensive set of UE…
Multi-domain Feature of Event-Related Potential Extracted by Nonnegative Tensor Factorization: 5 vs. 14 Electrodes EEG Data
2012
As nonnegative tensor factorization (NTF) is particularly useful for the problem of underdetermined linear transform model, we performed NTF on the EEG data recorded from 14 electrodes to extract the multi-domain feature of N170 which is a visual event-related potential (ERP), as well as 5 typical electrodes in occipital-temporal sites for N170 and in frontal-central sites for vertex positive potential (VPP) which is the counterpart of N170, respectively. We found that the multi-domain feature of N170 from 5 electrodes was very similar to that from 14 electrodes and more discriminative for different groups of participants than that of VPP from 5 electrodes. Hence, we conclude that when the …
Efficient Dense Disparity Map Reconstruction using Sparse Measurements
2018
International audience; In this paper, we propose a new stereo matching algorithm able to reconstruct efficiently a dense disparity maps from few sparse disparity measurements. The algorithm is initialized by sampling the reference image using the Simple Linear Iterative Clustering (SLIC) superpixel method. Then, a sparse disparity map is generated only for the obtained boundary pixels. The reconstruction of the entire disparity map is obtained through the scanline propagation method. Outliers were effectively removed using an adaptive vertical median filter. Experimental results were conducted on the standard and the new Middlebury datasets show that the proposed method produces high-quali…
The PAPIA system
1991
In 1983 an Italian research program was begun for the design, simulation and construction of a multiprocessor image processing system. After a first phase devoted to the comparison of suggested and existing systems and to the definition of a set of benchmarks, a new system was defined. The structure of this new system is introduced here: it is based on a fine-grained pyramid of processors built up by means of a pyramidal cell implemented on a VLSI multiprocessor chip. The peculiarities and the capabilities of the processing element are highlighted. The complete hardware and software system has been fully designed and is described. A first working prototype has been built and is now operatio…
A New Technique for Vibration-Based Diagnostics of Fatigued Structures Based on Damage Pattern Recognition via Minimization of Misclassification Prob…
2017
Vibration-based diagnostics provide various methods to detect, locate, and characterize damage in structural and mechanical systems by examining changes in measured vibration response. Research in vibration-based damage recognition has been rapidly expanding over the last few years. The basic idea behind this technology is that modal parameters (notably frequencies, mode shapes, and modal damping) are functions of the physical properties of the structure (mass, damping, and stiffness). Therefore, changes in the physical properties will cause detectable changes in the modal properties. In investigations, many techniques were applied to recognize damage in structural and mechanical systems, b…
Assessment of vine development according to available water resources by using remote sensing in La Mancha, Spain
1999
Abstract The relevance of growing vines under semiarid conditions is universally accepted because of its impacts on social, economic and environmental aspects. Improving the knowledge of the soil–plant–atmosphere system related to the expression of vine growth allows the study of vine cover in wide areas. Several aspects of vine growing under semiarid conditions, related to weather, soil, and plant cover are analysed in this paper. Once the ground truth is achieved, multitemporal studies by remote sensing are especially useful for vine growth monitoring. The purpose of this work is focussed on determining changes of vine cover development according to available water resources in relation t…
Applying pattern recognition methods plus quantum and physico-chemical molecular descriptors to analyze the anabolic activity of structurally diverse…
2008
The great cost associated with the development of new anabolic-androgenic steroid (AASs) makes necessary the development of computational methods that shorten the drug discovery pipeline. Toward this end, quantum, and physicochemical molecular descriptors, plus linear discriminant analysis (LDA) were used to analyze the anabolic/androgenic activity of structurally diverse steroids and to discover novel AASs, as well as also to give a structural interpretation of their anabolic-androgenic ratio (AAR). The obtained models are able to correctly classify 91.67% (86.27%) of the AASs in the training (test) sets, respectively. The results of predictions on the 10% full-out cross-validation test al…
Channel Capacity in Psychovisual Deep-Nets: Gaussianization Versus Kozachenko-Leonenko
2020
In this work, we quantify how neural networks designed from biology using no statistical training have a remarkable performance in information theoretic terms. Specifically, we address the question of the amount of information that can be extracted about the images from the different layers of psychophysically tuned deep networks. We show that analytical approaches are not possible, and we propose the use of two empirical estimators of capacity: the classical Kozachenko-Lonenko estimator and a recent estimator based on Gaussianization. Results show that networks purely based on visual psychophysics are extremely efficient in two aspects: (1) the internal representation of these networks dup…
Visualizing Confidence in Cluster-based Ensemble Weather Forecast Analyses
2020
In meteorology, cluster analysis is frequently used to determine representative trends in ensemble weather predictions in a selected spatio-temporal region, e.g., to reduce a set of ensemble members to simplify and improve their analysis. Identified clusters (i.e., groups of similar members), however, can be very sensitive to small changes of the selected region, so that clustering results can be misleading and bias subsequent analyses. In this article, we — a team of visualization scientists and meteorologists-deliver visual analytics solutions to analyze the sensitivity of clustering results with respect to changes of a selected region. We propose an interactive visual interface that enab…
Panel Discussion on “ how can Computer Science Contribute to the Solution of Problems Posed by Astronomers ?”
1985
A Panel was hold on June 3rd summarizing, in a way, the guide- lines and the aims of the Workshop. General questionswere addressed to M.Disney, E.Groth and D.Wells, who have expressed in the Workshop the point of view from Astronomy in the Sections “Data Analysis methodologies”, “Image processing” and “Systems for Data Analysis” respectively: