[PDF] Top 20 Deep learning for cardiac MR images analysis
Has 10000 "Deep learning for cardiac MR images analysis" found on our website. Below are the top 20 most common "Deep learning for cardiac MR images analysis".
Deep learning for cardiac MR images analysis
... CMR images, coming from a group of 55 patients, with 39 males and 16 females and ages between 12 and 92 years, collected along different imaging centers from Australia, Belgium, France, Germany, Japan, New ... See full document
80
Optimization of tagged MRI for quantification of liver stiffness using computer simulated data.
... of cardiac-induced strain in the liver at 3T and simulated tagged MR images with different grid tag patterns to evaluate the performance of the Harmonic Phase (HARP) image analysis method and ... See full document
8
Automatic indexing of web images: trends and challenges in deep learning context :: Brapci ::
... correlation analysis networks for two-view image recognition ...Correlation Analysis Network - CCANet), onde as imagens são representadas numa visão dupla de características por forma a aumentar a precisão ... See full document
21
Classificação de espécies florestais usando aprendizagem em profundidade (deep learning)
... Resumo: O principal objetivo deste projeto é o desenvolvimento de um sistema para o reconhecimento automático de espécies florestais usando aprendizagem profunda (Deep Learning). Neste tipo de sistema, uma ... See full document
9
Previsão na área farmacológica: modelos estatísticos vs Deep Learning
... de deep learning conseguiu alcançar melhores resultados que aqueles obtidos através dos modelos selecionados a partir do package forecast disponível no ... See full document
124
Deep-PRWIS: Periocular Recognition Without the Iris and Sclera Using Deep Learning Frameworks
... the learning phase, the CNN receives, for each periocular part, samples of different ocular classes, forcing it to conclude that such regions should not be considered in its response ...the learning and ... See full document
9
DEEP LEARNING PARA CLASSIFICAC¸ ˜AO HIER ´ARQUICA DE ELEMENTOS TRANSPON´IVEIS
... Machine Learning (AM) and Artificial Neu- ral Networks (RNA) trained using Deep Learning (DP) ...concepts. Deep Neural Networks have extend the state-of-art of many field of study, including ... See full document
125
Automatic transcription of music using deep learning techniques
... optimizers in order to discover the best combination of both. The learning rate is the hyperparameter that determines the amplitude of the changes when updating the weights. The momentum is a hyperparameter that ... See full document
116
Learning by observation of agent software images
... the learning and execution ...initial learning period increases as the Low- erConfidenceThreshold ...spends learning the less time it has to perform the ...a learning period that is long ... See full document
37
Daniel Souza Ferreira Magalhães 1,2 , Saad Mansoor3 , Ying Weng 3,4 , Enrico Ghizoni 2,5, Thiago Barbosa
... increased learning performance, and improved communications with patients or between ...3D images without any special glasses or equipment, describing a new way to obtain 3D visualization using sets of 2D ... See full document
5
Rev. Soc. Bras. Med. Trop. vol.36 número5
... resonance images (MRI) of the brain showed a left cerebellar lesion with mass effect compressing the surrounding ...Contrast-enhanced images showed a mass like structure and punctate nodules (Figures A and ... See full document
2
A deep learning approach for sentence classification of scientific abstracts
... novel deep learning architecture for ab- stract sentence ...proposed deep learning architecture to classify abstract corpus from other scientific domains and also to other sequential ... See full document
11
A robust deep convolutional neural network model for text categorization
... sentiment analysis tools is 70% [Gwet, ...Although deep learning models are inspired by the working principles of the human brain, they do not learn to ...from deep learning models, ... See full document
100
Some methods for sensitivity analysis of systems / networks
... Local sensitivity analysis (LSA) is mainly used to analyze local influence of parameters on model output. Gradients of parameters vs. model output can be achieved by using LSA. LSA is valuable to systems with ... See full document
8
Deep learning for single image super-resolution using residual image learning and multiple degradations
... residual learning to address the problem of generating a high-resolution image given a low-resolution image, commonly referred as single image super-resolution ... See full document
64
Analysis of the myocardial function using tagging MR
... Like any other method created with the goal of evaluating a specific behavior it is funda- mental to be able to recognize and distinguish a normal event from defective occurrences. In the specific case of the method ... See full document
68
Uma plataforma para revisão automática de literatura via técnicas de Text Mining
... São vários os modelos que têm vindo a ser aplicados, tais como Support Vector Machines (Ekbal & Bandyopadhyay, 2010), redes neuronais de diferentes arquiteturas (Lample, Ballesteros, Subramanian, Kawakami, & ... See full document
127
Developing deep learning computational tools for cancer using omics data
... Deep learning is a fascinating field of machine learning, and I would like to thank in first place to Professor Miguel Rocha for giving me the advice and the opportunity to take my first step into ... See full document
106
Biosignals learning and synthesis using deep neural networks
... In the ECG end, various research articles rely on its theoretical expression, such as the combination of cosine waves[8], the coupling of differential equation [1] or using delayed harmonic waves [9]. After the ... See full document
17
A FUZZY FRAMEWORK FOR SEGMENTATION, FEATURE MATCHING AND RETRIEVAL OF BRAIN MR IMAGES
... Thus the system was implemented successfully in MATLAB. The database contains 250 normal and 150 tumour images. The resolution of these images is 256x256.A query by example scheme of retrieval was used. ... See full document
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