Search results for "NVO"
showing 10 items of 2061 documents
MFNet: Multi-feature convolutional neural network for high-density crowd counting
2020
The crowd counting task involves the issue of security, so now more and more people are concerned about it. At present, the most difficult problem of population counting consists in: how to make the model distinguish human head features more finely in the densely populated area, such as head overlap and how to find a small-scale local head feature in an image with a wide range of population density. Facing these challenges, we propose a network for multiple feature convolutional neural network, which is called MFNet. It aims to get high-quality density maps in the high-density crowd scene, and at the same time to perform the task of the count and estimation of the crowd. In terms of crowd c…
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…
Assessment of tumor-infiltrating TCRV γ 9V δ 2 γδ lymphocyte abundance by deconvolution of human cancers microarrays
2017
Most human blood γδ cells are cytolytic TCRVγ9Vδ2+lymphocytes with antitumor activity. They are currently investigated in several clinical trials of cancer immunotherapy but so far, their tumor infiltration has not been systematically explored across human cancers. Novel algorithms allowing the deconvolution of bulk tumor transcriptomes to find the relative proportions of infiltrating leucocytes, such as CIBERSORT, should be appropriate for this aim but in practice they fail to accurately recognize γδ T lymphocytes. Here, by implementing machine learning from microarray data, we first improved the computational identification of blood-derived TCRVγ9Vδ2+γδ lymphocytes and then appl…
The emerging role of Notch pathway in ageing: Focus on the related mechanisms in age-related diseases
2016
Notch signaling is an evolutionarily conserved pathway, which is fundamental for the development of all tissues, organs and systems of human body. Recently, a considerable and still growing number of studies have highlighted the contribution of Notch signaling in various pathological processes of the adult life, such as age-related diseases. In particular, the Notch pathway has emerged as major player in the maintenance of tissue specific homeostasis, through the control of proliferation, migration, phenotypes and functions of tissue cells, as well as in the cross-talk between inflammatory cells and the innate immune system, and in onset of inflammatory age-related diseases. However, until …
Two simple criteria to estimate an objective's performance when imaging in non design tissue clearing solutions
2019
Tissue clearing techniques are undergoing a renaissance motivated by the need to image fluorescent neurons, and other cells, deep in the sample without physical sectioning. Optical transparency is achieved by equilibrating tissues with high refractive index (RI) solutions. When the microscope objective is not perfectly matched to the RI of the cleared sample, aberrations are introduced. We present two simple-to-calculate numerical criteria predicting: (i) the degradation in image quality (brightness and resolution) from optimal conditions of any clearing solution/objective combination; (ii) which objective, among several available, achieves the highest resolution in a given medium. We deriv…
In vitro effects of benzalkonium chloride and prostaglandins on human meibomian gland epithelial cells
2019
Abstract Purpose Benzalkonium chloride is the most widely used preservative in ophthalmic topical solutions. The aim of this study was to investigate the influence of BAC as a single substance or as a component of several commercially available ophthalmic solutions on meibomian gland epithelial cells in vitro. Materials and methods An immortalized human meibomian gland epithelial cell line (HMGEC) was used and cells were cultured in the absence or presence of fetal bovine serum to assess cell morphology, cell proliferation, cell viability (MTS assay) and impedance sensing (ECIS) after stimulation with BAC. Further, the viability of HMGECs stimulated with BAC-containing and BAC-free bimatopr…
Deep Learning Architectures for DNA Sequence Classification
2017
DNA sequence classification is a key task in a generic computational framework for biomedical data analysis, and in recent years several machine learning technique have been adopted to successful accomplish with this task. Anyway, the main difficulty behind the problem remains the feature selection process. Sequences do not have explicit features, and the commonly used representations introduce the main drawback of the high dimensionality. For sure, machine learning method devoted to supervised classification tasks are strongly dependent on the feature extraction step, and in order to build a good representation it is necessary to recognize and measure meaningful details of the items to cla…
Use of deep learning methods to translate drug-induced gene expression changes from rat to human primary hepatocytes
2020
In clinical trials, animal and cell line models are often used to evaluate the potential toxic effects of a novel compound or candidate drug before progressing to human trials. However, relating the results of animal and in vitro model exposures to relevant clinical outcomes in the human in vivo system still proves challenging, relying on often putative orthologs. In recent years, multiple studies have demonstrated that the repeated dose rodent bioassay, the current gold standard in the field, lacks sufficient sensitivity and specificity in predicting toxic effects of pharmaceuticals in humans. In this study, we evaluate the potential of deep learning techniques to translate the pattern of …
Using the Intervention Mapping protocol to develop a family-based intervention for improving lifestyle habits among overweight and obese children: st…
2016
Abstract Background In light of the high prevalence of childhood overweight and obesity, there is a need of developing effective prevention programs to address the rising prevalence and the concomitant health consequences. The main aim of the present study is to systematically develop and implement a tailored family-based intervention for improving lifestyle habits among overweight and obese children, aged 6–10 years old, enhancing parental self-efficacy, family engagement and parent-child interaction. A subsidiary aim of the intervention study is to reduce the prevalence of overweight and obesity among those participating in the intervention study. Methods/design The Intervention Mapping p…
PSPU-Net for Automatic Short Axis Cine MRI Segmentation of Left and Right Ventricles
2020
[EN] Characterization of the heart anatomy and function is mostly done with magnetic resonance image cine series. To achieve a correct characterization, the volume of the right and left ventricle need to be segmented, which is a timeconsuming task. We propose a new convolutional neural network architecture that combines U-net with PSP modules (PSPU-net) for the segmentation of left and right ventricle cavities and left ventricle myocardium in the diastolic frame of short-axis cine MRI images and compare its results against a classic 3D U-net architecture. We used a dataset containing 399 cases in total. The results showed higher quality results in both segmentation and final volume estimati…