Search results for "Cnn"
showing 10 items of 36 documents
La democracia amenazada
2001
Extensive molecular analysis of patients bearing CFTR-related disorders.
2012
Cystic fibrosis transmembrane conductance regulator (CFTR)–related disorders (CFTR-RDs) may present with pancreatic sufficiency, normal sweat test results, and better outcome. The detection rate of mutations is lower in CFTR-RD than in classic CF: mutations may be located in genes encoding proteins that interact with CFTR or support channel activity. We tested the whole CFTR coding regions in 99 CFTR-RD patients, looking for gene mutations in solute carrier (SLC) 26A and in epithelial Na channel (ENaC) in 33 patients who had unidentified mutations. CFTR analysis revealed 28 mutations, some of which are rare. Of these mutations, RT-PCR demonstrated that the novel 1525-1delG impairs exon 10 s…
DEVELOPMENT AND IMPLEMENTATION OF MACHINE LEARNING METHODS FOR THE IIF IMAGES ANALYSIS
2021
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…
Deep Convolutional Neural Network Based Object Detection Inference Acceleration Using FPGA
2022
Object detection is one of the most challenging yet essential computer vision research areas. It means labeling and localizing all known objects of interest on an input image using tightly fit rectangular bounding boxes around the objects. Object detection, having passed through several evolutions and progressions, nowadays relies on the successes of image classification networks based on deep convolutional neural networks. However, as the depth and complication of convolutional neural networks increased, detection speed reduced, and accuracy increased. Unfortunately, most computer vision applications, such as real-time object tracking on an embedded system, requires lightweight, fast and a…
Ēku 3D modeļu rekonstrukcija, izmantojot plakņu marķēšanas algoritmus un tālizpētes datus
2022
Pilsētvides problēmu risināšanā noderīgi ir ēku 3D (trīs dimensiju) modeļi, kas var tikt pielietoti pilsētas infrastruktūras plānošanā, scenāriju modelēšanā u.c. specifisku problēmu risināšanā. Darbs ir turpinājums autora bakalaura darbam, kurā tika piedāvāta metode ēku 3D modeļu izveidei. Tās galvenais trūkums ir nepieciešamība pēc lietotāja iejaukšanās, padarot metodi nepiemērotu plašai pilsētas 3D modelēšanai. Darba mērķis ir uzlabot jumta plakņu noteikšanas procesu, izmantojot mašīnmācīšanās metodes, un izstrādāt plašāk lietojamu ēku 3D modeļu ģenerēšanas algoritmu, kas būtu piemērots dažādām jumtu arhitektūrām. Darba rezultātā tiek apmācīts Mask R-CNN konvolūciju neironu tīkls jumta pl…
Novel SCNN1A gene splicing-site mutation causing autosomal recessive pseudohypoaldosteronism type 1 (PHA1) in two Italian patients belonging to the s…
2021
Abstract Introduction Pseudohypoaldosteronism type 1 (PHA1) is a rare genetic disease due to the peripheral resistance to aldosterone. Its clinical spectrum includes neonatal salt loss syndrome with hyponatremia and hypochloraemia, hyperkalemia, metabolic acidosis and increased plasmatic levels of aldosterone. Two genetically distinct forms of disease, renal and systemic, have been described, showing a wide clinical expressivity. Mutations in the genes encoding for the subunits of the epithelial sodium channels (ENaC) are responsible for generalized PHA1. Patients’ presentation We hereby report on two Italian patients with generalized PHA1, coming from the same small town in the center of S…
Evaluation of Deep Neural Networks for Semantic Segmentation of Prostate in T2W MRI
2020
In this paper, we present an evaluation of four encoder&ndash
THE “SALT-TASTING” NEWBORN
2021
Pseudohypoaldosteronism type 1 (PHA1) is a rare genetic disease due to the peripheral resistance to aldosterone. Clinical spectrum with neonatal onset includes salt loss, hyponatremia, hypochloraemia, hyperkalaemia, metabolic acidosis and increased plasmatic levels of aldosterone. Two forms of the disease - renal and systemic – have been described, which are genetically distinct and with wide clinical expressivity. The most severe generalized PHA1 is caused by mutations in the genes encoding for the subunits of the epithelial sodium channels (ENaC). The paper reports the case of a newborn of the first pregnancy of healthy and consanguineous Sicilian parents, with a clinical and hormonal pic…
Estimating Grass Sward Quality and Quantity Parameters Using Drone Remote Sensing with Deep Neural Networks
2022
Funding Information: Funding: This research was funded by Academy of Finland ICT 2023 Smart‐HSI—“Smart hyper‐ spectral imaging solutions for new era in Earth and planetary observations” (Decision no. 335612), by the European Agricultural Fund for Rural Development: Europe investing in rural areas, Pohjois‐ Savon Ely‐keskus (Grant no. 145346) and by the European Regional Development Fund for “Cyber‐ Grass I—Introduction to remote sensing and artificial intelligence assisted silage production” pro‐ ject (ID 20302863) in European Union Interreg Botnia‐Atlantica programme. This research was car‐ ried out in affiliation with the Academy of Finland Flagship “Forest‐Human‐Machine Interplay— Buildi…