[PDF] Top 20 Detection of abnormalities in ECG using Deep Learning
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Detection of abnormalities in ECG using Deep Learning
... event detection in ECG has been ongoing for many years and, consequently, many approaches have been developed to tackle this chal- ...area of research is mostly motivated by the difficulty ... See full document
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Convolutional neural networks for cell detection and counting : a case study of human cell quantification in zebrafish xenografts using deep learning object detection techniques
... sister in law, because they were the ones who suffer most this path with ...years of patience and full support in my decisions, all the love, and ...words of wisdom, pressure, confidence, and ... See full document
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Recognition and Tracking of Vehicles in Highways using Deep Learning
... proposed in ( M.A.AMARAL et al. , 2015 ), for detection and tracking of multiple moving vehicles in the environment around an autonomous vehicle using a Light Detec- tion and Ranging ... See full document
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Detection of production defects using Machine Learning based Image Classification Algorithms
... quantity of a dataset is the most crucial factor for the successful solving of a task via a machine learning ...grown in popularity used with deep learning models specifically to ... See full document
65
Improving cyberthreat discovery in open source intelligence using deep learning techniques
... overview of previous work done in regards to threat intelligence from ...events in near real-time over the Twitter Stream. The framework makes use of the Twitter API and a list of ... See full document
83
Computer Vision: Object recognition with deep learning applied to fashion items detection in images
... object detection has a two-step detection tactic that allows giving more importance to the free text titles on Pinterest ...characteristic of the Pinterest is the possibility of pin an image, ... See full document
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A Deep Learning Approach for Red Lesions Detection in Video Capsule Endoscopies
... diagnosis of small bowel diseases. However, a single examination has up to 10 h of video and requires between 30–120 min to ...accuracy of the diagnosis. In this paper, an evaluation of ... See full document
9
Deep Learning for EEG Analysis in Epilepsy
... retrained using Set B and class weights 100:1 to assess the difference in performance in the IED detection ...improvement in the performance of all the models on the test ...set ... See full document
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Chimpanzee face recognition from videos in the wild using deep learning
... efficacy of using deep neural network architectures for a direct biological application: the detection, tracking, and recognition of individual animals in longitudinal video ... See full document
10
Biosignals learning and synthesis using deep neural networks
... Some of the R peaks do not have the final form Finally, after 80 epochs, even though there is a latency in between some waves, it is possible to see the notion of periodicity, even though it is not ... See full document
17
Intelligent System for Detection of Abnormalities in Human Cancerous Cells and Tissues
... [2] of three ML (Machine Learning) neural network based algorithms was conducted to deeply analyze thyroid disease ...by using Scaled Conjugate Gradient, quasi-Newton method, Gradient Descent with ... See full document
7
Age Estimation using Deep Learning on 3D Facial Features
... cloud of the face depicted in the picture means we have a 3D representation of the face of the individual present in the ...projection of the face was available which was the ... See full document
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Deep Learning in Melanoma Detection
... review of the state-of-the-art in deep learning and transfer learning approaches was done, detailing some of its advances since the origin of the term deep ... See full document
77
Deep learning techniques for grapevine variety classification using natural images
... machine learning algorithm, as: (i) model-based approach, in which feature detection, extraction, and encoding methods for computing characteristic feature vectors is initially a problem-specific ... See full document
150
ECG-based heartbeat classification for arrhythmia detection : a survey.
... activity of the heart and has been widely used for detecting heart diseases due to its simplicity and non-invasive ...signal of each heartbeat, i.e., the combination of action impulse waveforms ... See full document
21
ECG Biometrics using Deep Neural Networks
... seen in Figure 6.4, more epochs of training can lead to improved ...choice of 10 training epochs was made to avoid ...instability in later epochs, values of learning rate ...used ... See full document
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Deep learning for single image super-resolution using residual image learning and multiple degradations
... introduced in (ZHANG; ZUO; ZHANG, 2018) and a GAN-based model for super resolution, SRGAN (Super-Resolution GAN), developed by (LEDIG et ...proposed learning algorithm makes use of these ... See full document
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5G MIMO and LIDAR data for machine learning: mmWave beam-selection using deep learning
... pursuit of the masters degree, other publications were done in topics related to deep learning and other to community networks, such as: "Deep Learning in RAT and Mod- ... See full document
61
Detection and Classification of Obstacles for Autonomous Vessels Using Machine Learning
... the detection and classification of obstacles (accord- ing to their size, shape and especially distance to the autonomous vessel) on the surface of the water using machine learning ... See full document
70
Developing deep learning computational tools for cancer using omics data
... amount of epochs ...pipeline of 10-fold cross validation may not be the best one, suggesting that some overfitting could be ...[66] of 10 x 5-Fold cross validation would be ... See full document
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