Surfing internet becomes common now-a-days that gave a chance for intruders to steal information. Therefore security is very important to detect any unwanted activities by using intrusion detection system. Intrusion d...
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The proceedings contain 15 papers. The topics discussed include: identifying optimal features for multi-channel acoustic scene classification;analysis of CNN architectures for pose estimation of noisy 3-D face images;...
ISBN:
(纸本)9781728138732
The proceedings contain 15 papers. The topics discussed include: identifying optimal features for multi-channel acoustic scene classification;analysis of CNN architectures for pose estimation of noisy 3-D face images;meteorite hunting using deep learning and UAVs;real-time dynamic security for ProSe in 5G;image steganography using YCbCr color space and matrix pattern;cost effective real time vision interface for off line simulation of Fanuc robots;smart healthcare systems on improving the efficiency of healthcare services;time-domain color mapping for color vision deficiency assistive technology;and spatio-temporal analysis andmachinelearning for traffic accidents prediction.
The problem of epilepsy has grown exponentially and is now considered as one of the most prevailing neurological disorders affecting around 50 million people around the globe. Epilepsy is identified by analyzing the i...
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Word embeddings are an efficient way of representing text such that they can be used by different machinelearning Algorithms. Word2Vec is one such word embedding model. Although it is highly efficient, this model can...
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In this paper, automatic classification of Atrial Fibrillation (AF) based on single lead ECG signal was proposed using three different classification algorithm AdaBoost, K-Nearest Neighbors (KNN) and Support Vector Ma...
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ISBN:
(纸本)9781450388412
In this paper, automatic classification of Atrial Fibrillation (AF) based on single lead ECG signal was proposed using three different classification algorithm AdaBoost, K-Nearest Neighbors (KNN) and Support Vector machine (SVM). SMOTE technique was applied as data oversampling techniques. Many features were extracted and Minimum Redundancy Maximum Relevance (MRMR) algorithm was used to select relevant features. 5834 records were selected from the Physionet Challenge 2017 dataset for this experiment. Classification using oversampling technique yields best results for all classifiers involved. AdaBoost on oversampling data yields the best accuracy of 98.8%.
We describe a method to learn the flight dynamics of an unmanned aerial vehicle (UAV). This follows the recent trend to adopt a learning approach to Visual Odometry (VO). Our novelty is the inclusion of a module to co...
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ISBN:
(纸本)9781538609699
We describe a method to learn the flight dynamics of an unmanned aerial vehicle (UAV). This follows the recent trend to adopt a learning approach to Visual Odometry (VO). Our novelty is the inclusion of a module to compensate for the roll pitch angular motion of the UAV due to body vibration. This is a significant deviation from most existing works that are applied to land vehicles. We empirically verify our results on real flight data, showing that after compensating for angular vibration, the ego-motion of the UAV can be robustly estimated even by using simple regression tools. This enables the advantages of learning based VO to be within reach of the UAV community.
In today’s world, machinelearning is an emerging technology which is being used extensively in different domains. In order to offer effective solutions in the broad area of computer security with the use of machine ...
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Text to image transformation for input to neural networks requires intermediate steps. This paper attempts to present a new approach to pixel normalization so as to convert textual data into image, suitable as input f...
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ISBN:
(纸本)9781509044429
Text to image transformation for input to neural networks requires intermediate steps. This paper attempts to present a new approach to pixel normalization so as to convert textual data into image, suitable as input for neural networks. This method can be further improved by its Graphics processing Unit (GPU) implementation to provide significant speedup in computational time.
In the era of big data, software algorithms are improving rapidly, andmachinelearning algorithms are also widely used. In doing so, transmitting signals from quantum devices will also contribute to research on machi...
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Technology is growing exponentially than ever before;it helps us to make unforeseen progress but at the same time these advancements also pose a grave danger to software systems in terms of security. While paving a pa...
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