Search results for "Computer Vision"

Cover Feature: Alkali Blues: Blue‐Emissive Alkali Metal Pyrrolates (Chem. Eur. J. 26/2019)

2019

Implementing a Margolus Neighborhood Cellular Automata on a FPGA

2003

Margolus neighborhood is the easiest form of designing Cellular Automata Rules with features such as invertibility or particle conserving. In this paper we introduce a notation to describe completely a rule based on this neighborhood and implement it in two ways: The first corresponds to a classical RAM-based implementation, while the second, based on concurrent cells, is useful for smaller systems in which time is a critical parameter. This implementation has the feature that the evolution of all the cells in the design is performed in the same clock cycle.

Adaptive Distance-Based Pooling in Convolutional Neural Networks for Audio Event Classification

2020

In the last years, deep convolutional neural networks have become a standard for the development of state-of-the-art audio classification systems, taking the lead over traditional approaches based on feature engineering. While they are capable of achieving human performance under certain scenarios, it has been shown that their accuracy is severely degraded when the systems are tested over noisy or weakly segmented events. Although better generalization could be obtained by increasing the size of the training dataset, e.g. by applying data augmentation techniques, this also leads to longer and more complex training procedures. In this article, we propose a new type of pooling layer aimed at …

Combining feature extraction and expansion to improve classification based similarity learning

2017

Abstract Metric learning has been shown to outperform standard classification based similarity learning in a number of different contexts. In this paper, we show that the performance of classification similarity learning strongly depends on the data format used to learn the model. We then present an Enriched Classification Similarity Learning method that follows a hybrid approach that combines both feature extraction and feature expansion. In particular, we propose a data transformation and the use of a set of standard distances to supplement the information provided by the feature vectors of the training samples. The method is compared to state-of-the-art feature extraction and metric lear…

Local electrical characterisation of human atrial fibrillation

2002

The rate of success of radio-frequency catheter ablation in the treatment of atrial fibrillation may be significantly improved by evaluating the local electrical properties of the atrial tissue. The aim of this study is the development of an automatic procedure for the characterisation of the local electrical activity during atrial fibrillation and the comparison of its performance with the manual analysis. The adopted procedures were the semi-automatic measurement of the local fibrillation intervals (A-A intervals) and the manual electrogram classification following the criteria suggested by Wells (1978) or Konings (1997). Two methods have been used: Principal Component Analysis and Cluste…

Testing the X-IFU calibration requirements: an example for quantum efficiency and energy resolution

2018

With its array of 3840 Transition Edge Sensors (TESs) operated at 90 mK, the X-Ray Integral Field Unit (X-IFU) on board the ESA L2 mission Athena will provide spatially resolved high-resolution spectroscopy (2.5 eV FWHM up to 7 keV) over the 0.2 to 12 keV bandpass. The in-flight performance of the X-IFU will be strongly affected by the calibration of the instrument. Uncertainties in the knowledge of the overall system, from the filter transmission to the energy scale, may introduce systematic errors in the data, which could potentially compromise science objectives - notably those involving line characterisation e.g. turbulence velocity measurements - if not properly accounted for. Defining…

The performance of the ATHENA X-ray Integral Field Unit

2018

The X-ray Integral Field Unit (X-IFU) is a next generation microcalorimeter planned for launch onboard the Athena observatory. Operating a matrix of 3840 superconducting Transition Edge Sensors at 90 mK, it will provide unprecedented spectro-imaging capabilities (2.5 eV resolution, for a field of view of 5') in the soft X-ray band (0.2 up to 12 keV), enabling breakthrough science. The definition of the instrument evolved along the phase A study and we present here an overview of its predicted performances and their modeling, illustrating how the design of the X-IFU meets its top-level scientific requirements. This article notably covers the energy resolution, count-rate capability, quantum …

Performance of Fine-Tuning Convolutional Neural Networks for HEp-2 Image Classification

2020

The search for anti-nucleus antibodies (ANA) represents a fundamental step in the diagnosis of autoimmune diseases. The test considered the gold standard for ANA research is indirect immunofluorescence (IIF). The best substrate for ANA detection is provided by Human Epithelial type 2 (HEp-2) cells. The first phase of HEp-2 type image analysis involves the classification of fluorescence intensity in the positive/negative classes. However, the analysis of IIF images is difficult to perform and particularly dependent on the experience of the immunologist. For this reason, the interest of the scientific community in finding relevant technological solutions to the problem has been high. Deep lea…

RECOGNIZABLE PICTURE LANGUAGES

1992

The purpose of this paper is to propose a new notion of recognizability for picture (two-dimensional) languages extending the characterization of one-dimensional recognizable languages in terms of local languages and alphabetic mappings. We first introduce the family of local picture languages (denoted by LOC) and, in particular, prove the undecidability of the emptiness problem. Then we define the new family of recognizable picture languages (denoted by REC). We study some combinatorial and language theoretic properties of REC such as ambiguity, closure properties or undecidability results. Finally we compare the family REC with the classical families of languages recognized by four-way a…

Combining Top-down and Bottom-up Visual Saliency for Firearms Localization

2014

Object detection is one of the most challenging issues for computer vision researchers. The analysis of the human visual attention mechanisms can help automatic inspection systems, in order to discard useless information and improving performances and efficiency. In this paper we proposed our attention based method to estimate firearms position in images of people holding firearms. Both top-down and bottom-up mechanisms are involved in our system. The bottom-up analysis is based on a state-of-the-art approach. The top-down analysis is based on the construction of a probabilistic model of the firearms position with respect to the people’s face position. This model has been created by analyzi…