Search results for "pattern"
showing 10 items of 4203 documents
Nanostructured molecular surfaces: advances in investigation and patterning tools
2009
This feature article is aimed to showcase advanced soft and radiationless nanotools for the morphological characterization and for the preparation/modification of molecular surfaces, namely solid supported ultrathin films not exceeding 1–2 molecular layers. As to the characterization, the development of dynamic scanning force microscopy in attractive regime is presented as an important progress at least as far as it concerns imaging of nanoscale features of molecular surfaces with minimal probe–sample physical interaction. To date, this tool has been applied only by a few groups in spite of its larger resolution and image quality than the conventional scanning probe methods. As to the prepa…
Automatic landmark detection and 3D Face data extraction
2017
Abstract This paper contributes to 3D facial synthesis by presenting a novel method for parameterization using Landmark Point detection. The approach presented aims at improving facial recognition even in varying facial expressions, and missing data in 3D facial models. As such, the prime objective was to develop an automatically embedded process that can detect any frontal face in 3D face recognition systems, with face segmentation and surface curvature information. Using the hybrid interpolation method, experiments on facial landmarks were performed on 4950 images from Face Recognition Grand Challenge database (FRGC). Distinctive facial landmarks from the nose–tips, Limits mouth and two e…
Probabilistic Corner Detection for Facial Feature Extraction
2009
After more than 35 years of resarch, face processing is considered nowadays as one of the most important application of image analysis. It can be considered as a collection of problems (i.e., face detection, normalization, recognition and so on) each of which can be treated separately. Some face detection and face recognition techniques have reached a certain level of maturity, however facial feature extraction still represents the bottleneck of the entire process. In this paper we present a novel facial feature extraction approach that could be used for normalizing Viola-Jones detected faces and let them be recognized by an appearance-based face recognition method. For each observed featur…
Wie vergleichbar sind vergleichbare und parallele Fachkorpora? Ergebnisse einer Pilotstudie zum Sprachenpaar dt./frz. in Finanzdiskursen
2021
International audience
Remote heart rate variability for emotional state monitoring
2018
International audience; Several researches have been conducted to recognize emotions using various modalities such as facial expressions , gestures, speech or physiological signals. Among all these modalities, physiological signals are especially interesting because they are mainly controlled by the autonomic nervous system. It has been shown for example that there is an undeniable relationship between emotional state and Heart Rate Variability (HRV). In this paper, we present a methodology to monitor emotional state from physiological signals acquired remotely. The method is based on a remote photoplethysmography (rPPG) algorithm that estimates remote Heart Rate Variability (rHRV) using a …
Coarse scales are sufficient for efficient categorization of emotional facial expressions: Evidence from neural computation
2010
The human perceptual system performs rapid processing within the early visual system: low spatial frequency information is processed rapidly through magnocellular layers, whereas the parvocellular layers process all the spatial frequencies more slowly. The purpose of the present paper is to test the usefulness of low spatial frequency (LSF) information compared to high spatial frequency (HSF) and broad spatial frequency (BSF) visual stimuli in a classification task of emotional facial expressions (EFE) by artificial neural networks. The connectionist modeling results show that an LSF information provided by the frequency domain is sufficient for a distributed neural network to correctly cla…
How endogenous asymmetries in interregional market access trigger regional divergence
2005
International audience; We investigate how asymmetric trade patterns in differentiated products affect the regional distribution of economic activities. The asymmetry in interregional market access is an endogenous result of price competition and industry location and arises for intermediate values of trade costs. We show that the emergence of one-way trade in differentiated products gives rise to strong agglomeration forces and leads to the absorption of the smaller region's industry by the larger region. The number of spatial equilibria increases once the pattern of trade is endogenously accounted for.
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 …
Classification of Heart Sounds Using Convolutional Neural Network
2020
Heart sounds play an important role in the diagnosis of cardiac conditions. Due to the low signal-to-noise ratio (SNR), it is problematic and time-consuming for experts to discriminate different kinds of heart sounds. Thus, objective classification of heart sounds is essential. In this study, we combined a conventional feature engineering method with deep learning algorithms to automatically classify normal and abnormal heart sounds. First, 497 features were extracted from eight domains. Then, we fed these features into the designed convolutional neural network (CNN), in which the fully connected layers that are usually used before the classification layer were replaced with a global averag…
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…