Search results for "tomate"
showing 10 items of 261 documents
Automated Diagnostics of Retinal Pathologies Using OCT Volumes
2020
The leading cause of blindness in the population could mostly be the degeneration of the retina caused by the diabetic-related problems and the aging issue. Diabetic retinopathy (DR) and diabetic macular edema (DME) are the main direct causes of vision problems in the labor age citizens of most advanced countries. The elevated number of diabetic people globally indicates that DME and DR will remain to be the principal factor to partial or total vision loss, which affects the lives quality of patients for many years to come and threaten their lives. Therefore, early detection followed by fast treatment procedures of persons with diabetic-related diseases is significant in preventing optical …
Simulation-Based Analysis of "What-If" Scenarios with Connected and Automated Vehicles Navigating Roundabouts.
2022
Despite the potential of connected and automated vehicles (CAVs), there are still many open questions on how road capacity can be influenced and what methods can be used to assess its expected benefits in the progressive transition towards fully cooperative driving. This paper contributes to a better understanding of the benefits of CAV technologies by investigating mobility-related issues of automated vehicles operating with a cooperative adaptive cruise control system on roundabout efficiency using microscopic traffic simulation. The availability of the adjustment factors for CAVs provided by the 2022 Highway Capacity Manual allowed to adjust the entry capacity equations to reflect the pr…
Multi-aperture beamforming for automated large structure inspection using ultrasonic phased arrays
2019
Increasing the inspection quality and speed is essential in manufacturing applications, especially for large structures (e.g. modern aircrafts). Traditional ultrasonic manual scanning can be comprehensive, but lacks repeatability and is time-consuming. Several robotic non-destructive testing systems have been developed in recent years. Although high inspection rates have been achieved by the use of robotic arms, there is the need to furtherly increase the inspection speeds, to cope with the current industrial demands. For systems delivering robotic ultrasonic inspection through phased array probes, the current bottleneck is given by the time required to electrically fire all elements of the…
Deep learning and process understanding for data-driven Earth system science
2017
Machine learning approaches are increasingly used to extract patterns and insights from the ever-increasing stream of geospatial data, but current approaches may not be optimal when system behaviour is dominated by spatial or temporal context. Here, rather than amending classical machine learning, we argue that these contextual cues should be used as part of deep learning (an approach that is able to extract spatio-temporal features automatically) to gain further process understanding of Earth system science problems, improving the predictive ability of seasonal forecasting and modelling of long-range spatial connections across multiple timescales, for example. The next step will be a hybri…
Genesis of amorphous calcium carbonate containing alveolar plates in the ciliate Coleps hirtus (Ciliophora, Prostomatea).
2013
7 pages; International audience; In the protist world, the ciliate Coleps hirtus (phylum Ciliophora, class Prostomatea) synthesizes a peculiar biomineralized test made of alveolar plates, structures located within alveolar vesicles at the cell cortex. Alveolar plates are arranged by overlapping like an armor and they are thought to protect and/or stiffen the cell. Although their morphology is species-specific and of complex architecture, so far almost nothing is known about their genesis, their structure and their elemental and mineral composition. We investigated the genesis of new alveolar plates after cell division and examined cells and isolated alveolar plates by electron microscopy, e…
On the use of Denoising Autoencoders and Deep Convolutional Adversarial Networks for Automated Removal of Date Stamps
2019
Master's thesis Information- and communication technology IKT590 - University of Agder 2019 This thesis investigates to what extent the deep learning models such as DenoisingAutoencoder (DAE) and Deep Convolution General Adversarial Net (DCGAN)automate the removal of the date stamps from images with high resolution whilepreserving the rest of the images. Both DAE and DCGAN algorithms are im-plemented with Convolutional Neural Networks (CNN). The DAE algorithm canperform this task with entirely satisfactory results. The DAE can reconstruct theoriginal images from corrupted inputs with date stamps. While DCGAN deliverspoor yet interesting results. The images generated by the DCGAN are quite d…
Index-based triangulation method for efficient generation of large three-dimensional ultrasonic C-scans
2018
The demand for high-speed ultrasonic scanning of large and complex components is driven by a desire to reduce production bottlenecks during the non-destructive evaluation (NDE) of critical parts. Emerging systems (including robotic inspection) allow for the collection of large volumes of data in short time spans, compared to existing inspection systems. To maximise throughput, it is crucial that the reconstructed inspection datasets are generated and evaluated rapidly without loss of detail. This requires new data visualisation and analysis tools capable of mapping complex geometries while guaranteeing full coverage. This paper presents an entirely new approach for the visualisation of thre…
3D segmentation of abdominal aorta from CT-scan and MR images
2012
International audience; We designed a generic method for segmenting the aneurismal sac of an abdominal aortic aneurysm (AAA) both from multi-slice MR and CT-scan examinations. It is a semi-automatic method requiring little human intervention and based on graph cut theory to segment the lumen interface and the aortic wall of AAAs. Our segmentation method works independently on MRI and CT-scan volumes and has been tested on a 44 patient dataset and 10 synthetic images. Segmentation and maximum diameter estimation were compared to manual tracing from 4 experts. An inter-observer study was performed in order to measure the variability range of a human observer. Based on three metrics (the maxim…
Managing Multi-center Flow Cytometry Data for Immune Monitoring.
2014
With the recent results of promising cancer vaccines and immunotherapy 1 – 5 , immune monitoring has become increasingly relevant for measuring treatment-induced effects on T cells, and an essential tool for shedding light on the mechanisms responsible for a successful treatment. Flow cytometry is the canonical multi-parameter assay for the fine characterization of single cells in solution, and is ubiquitously used in pre-clinical tumor immunology and in cancer immunotherapy trials. Current state-of-the-art polychromatic flow cytometry involves multi-step, multi-reagent assays followed by sample acquisition on sophisticated instruments capable of capturing up to 20 parameters per cell at a…
Automated Flow Cytometric Analysis of Blood Cells in Cerebrospinal Fluid
2004
We compared the performance of an automated method for obtaining RBC and WBC counts and WBC differential counts in cerebrospinal fluid (CSF) samples with the reference manual method. Results from 325 samples from 10 worldwide clinical sites were used to demonstrate the accuracy, precision, and linearity of the method. Accuracy statistics for absolute cell counts showed a high correlation between methods, with correlation coefficients for all reportable absolute counts greater than 0.9. Linearity results demonstrated that the method provides accurate results throughout the reportable ranges, including clinical decision points for WBCs of 0 to 10/μL. Interassay precision and intra-assay preci…