Search results for " IMAGE"
showing 10 items of 3936 documents
Image-Evoked Affect and its Impact on Eeg-Based Biometrics
2019
Electroencephalography (EEG) signals provide a representation of the brain’s activity patterns and have been recently exploited for user identification and authentication due to their uniqueness and their robustness to interception and artificial replication. Nevertheless, such signals are commonly affected by the individual’s emotional state. In this work, we examine the use of images as stimulus for acquiring EEG signals and study whether the use of images that evoke similar emotional responses leads to higher identification accuracy compared to images that evoke different emotional responses. Results show that identification accuracy increases when the system is trained with EEG recordin…
ES1D: A Deep Network for EEG-Based Subject Identification
2017
Security systems are starting to meet new technologies and new machine learning techniques, and a variety of methods to identify individuals from physiological signals have been developed. In this paper, we present ESID, a deep learning approach to identify subjects from electroencephalogram (EEG) signals captured by using a low cost device. The system consists of a Convolutional Neural Network (CNN), which is fed with the power spectral density of different EEG recordings belonging to different individuals. The network is trained for a period of one million iterations, in order to learn features related to local patterns in the spectral domain of the original signal. The performance of the…
A Fast Multiresolution Approach Useful for Retinal Image Segmentation
2018
Retinal diseases such as retinopathy of prematurity (ROP), diabetic and hypertensive retinopathy present several deformities of fundus oculi which can be analyzed both during screening and monitoring such as the increase of tortuosity, lesions of tissues, exudates and hemorrhages. In particular, one of the first morphological changes of vessel structures is the increase of tortuosity. The aim of this work is the enhancement and the detection of the principal characteristics in retinal image by exploiting a non-supervised and automated methodology. With respect to the well-known image analysis through Gabor or Gaussian filters, our approach uses a filter bank that resembles the “à trous” wav…
Factors Affecting Sexual Function and Body Image of Early-Stage Breast Cancer Survivors in Poland: A Short-Term Observation
2019
Abstract Introduction Knowing the important factors influencing sexual function and body image might facilitate the recovery process of breast cancer survivors. Surgery type, relationship quality, and partner support might be modified to create a space for psychosexual intervention. Patients and Methods This retrospective questionnaire-based study was performed on 128 women aged 18 to 65 years who were free of disease at time of study entry and who underwent surgical treatment for breast cancer. Diagnostic and Statistical Manual of Mental Disorders criteria were used to assessed female sexual dysfunction (FSD). Changes in Sexual Functioning Questionnaire (CSFQ) were used to measure sexual f…
Infrared microspectroscopic determination of collagen cross-links in articular cartilage
2017
Collagen forms an organized network in articular cartilage to give tensile stiffness to the tissue. Due to its long half-life, collagen is susceptible to cross-links caused by advanced glycation end-products. The current standard method for determination of cross-link concentrations in tissues is the destructive high-performance liquid chromatography (HPLC). The aim of this study was to analyze the cross-link concentrations nondestructively from standard unstained histological articular cartilage sections by using Fourier transform infrared (FTIR) microspectroscopy. Half of the bovine articular cartilage samples ( n = 27 ) were treated with threose to increase the collagen cross-linking whi…
Progressive derivation of serially homologous neuroblast lineages in the gnathal CNS of Drosophila
2018
Along the anterior-posterior axis the central nervous system is subdivided into segmental units (neuromeres) the composition of which is adapted to their region-specific functional requirements. In Drosophila melanogaster each neuromere is formed by a specific set of identified neural stem cells (neuroblasts, NBs). In the thoracic and anterior abdominal region of the embryonic ventral nerve cord segmental sets of NBs resemble the ground state (2nd thoracic segment, which does not require input of homeotic genes), and serial (segmental) homologs generate similar types of lineages. The three gnathal head segments form a transitional zone between the brain and the ventral nerve cord. It has be…
Quantum clustering in non-spherical data distributions: Finding a suitable number of clusters
2017
Quantum Clustering (QC) provides an alternative approach to clustering algorithms, several of which are based on geometric relationships between data points. Instead, QC makes use of quantum mechanics concepts to find structures (clusters) in data sets by finding the minima of a quantum potential. The starting point of QC is a Parzen estimator with a fixed length scale, which significantly affects the final cluster allocation. This dependence on an adjustable parameter is common to other methods. We propose a framework to find suitable values of the length parameter σ by optimising twin measures of cluster separation and consistency for a given cluster number. This is an extension of the Se…
Improving Docking Performance Using Negative Image-Based Rescoring
2017
Despite the large computational costs of molecular docking, the default scoring functions are often unable to recognize the active hits from the inactive molecules in large-scale virtual screening experiments. Thus, even though a correct binding pose might be sampled during the docking, the active compound or its biologically relevant pose is not necessarily given high enough score to arouse the attention. Various rescoring and post-processing approaches have emerged for improving the docking performance. Here, it is shown that the very early enrichment (number of actives scored higher than 1% of the highest ranked decoys) can be improved on average 2.5-fold or even 8.7-fold by comparing th…
Revealing community structures by ensemble clustering using group diffusion
2018
We propose an ensemble clustering approach using group diffusion to reveal community structures in data. We represent data points as a directed graph and assume each data point belong to single cluster membership instead of multiple memberships. The method is based on the concept of ensemble group diffusion with a parameter to represent diffusion depth in clustering. The ability to modulate the diffusion-depth parameter by varying it within a certain interval allows for more accurate construction of clusters. Depending on the value of the diffusion-depth parameter, the presented approach can determine very well both local clusters and global structure of data. At the same time, the ability …
Automatic detection of hemangiomas using unsupervised segmentation of regions of interest
2016
In this paper we compare the performances of three automatic methods of identifying hemangioma regions in images: 1) unsupervised segmentation using the Otsu method, 2) Fuzzy C-means clustering (FCM) and 3) an improved region growing algorithm based on FCM (RG-FCM). For each image, the starting point of the algorithms is a rectangular region of interest (ROI) containing the hemangioma. For computing the performances of each method, the ROIs had been manually labeled in 2 classes: pixels of hemangioma and pixels of non-hemangioma. The computed scores are given separately for each image, as well as global performances across all ROIs for both classes. The best classification of non-hemangioma…