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At present, shallow characteristics are usually utilized to represent the distributed features of text for Chinese spam classification, causing the problem of inexact text vector representation and low classification performance. A novel Chinese spam classification method based on weighted distributed feature is proposed by combining the features of TF-IDF weighted algorithm with the distributed text-based...
For face recognition systems, impostors can obtain legal identity authentication by presenting the printed images, the downloaded images or candid videos to the sensor. In this paper, an enhanced face local binary feature (ELBP) of a face map is extracted as a classification feature to identify whether the face map is a real face or a fake face. Compared with the dynamic or static methods proposed...
The modular multilevel converter with series and parallel connectivity was shown to provide advantages in several industrial applications. Its reliability largely depends on the absence of failures in the power semiconductors. We propose and analyze a fault-diagnosis technique to identify shorted switches based on features generated through wavelet transform of the converter output and subsequent...
In view of the support vector machine (SVM) model applied in vibrant fault diagnosis for hydro-turbine generating unit, it exists problems of parameter settings and classification-plane incline due to unequal sample, which leads to lower diagnosis accuracy. As a new bionic intelligent optimization algorithm for glowworm swarm optimization(GSO), it has the characteristics of strong versatility and...
Acoustic event detection (AED) is currently a very active research area with multiple applications in the development of smart acoustic spaces. In this context, the advances brought by Internet of Things (IoT) platforms where multiple distributed microphones are available have also contributed to this interest. In such scenarios, the use of data fusion techniques merging information from several sensors...
A Brain-Computer Interface (BCI) speller system based on the Steady-State Visually Evoked Potentials (SSVEP) paradigm is presented. The potentials are elicited through the gaze fixation at one out of the four checkerboards shown on screen, which are flickering at 5, 12, 15 and 20 Hz. After the feature extraction, two dimensionality reduction algorithms, Principal Components Analysis (PCA) and Linear...
The emergence of medical social media has made it possible for more and more patients to share their views and experiences on the medical care platform. These subjective texts contains patients' evaluation information for doctors and can be analyzed to provide rich decision-making information for patients and hospitals. Therefore, we propose a LSTM (Long Short Term Memory) based text sentiment classification...
Despite widespread use of commercial anti-virus products, the number of malicious files detected on home and corporate computers continues to increase at a significant rate. Recently, anti-virus companies have started investing in machine learning solutions to augment signatures manually designed by analysts. A malicious file's determination is often represented as a hierarchical structure consisting...
SVM (Support Vector Machine), a state of the art classifier model is implemented on a computational mobile platform and its performances are evaluated against a low complexity classifier such as SFSVC (Super Fast Vector Support Classifier) on the same platform. For a better comparison, similar implementation for the two architectures are considered, such as using the same basic linear algebra library...
Recently, the combination of classification systems with semi-supervised learning has attracted researchers in several fields. Usually, for tasks with high complexity such as handwriting based age prediction, individual systems, using one classifier associated with specific data features, cannot provide satisfactory performance. In this paper, we investigate the contribution of the Co-training approach,...
This paper presents improvements in terms of accuracy for shape object classification using a new low complexity method compared to previous implementation [1]. The method is using echoes generated by a JAVA platform capable of emulate sound propagation in a controlled 2D virtual environment [2][3]. Echoes originate from the ultrasonic waves generated inside a virtual environment which contains geometrical...
In order to solve the problem of lacking shear wave velocity information in oil and gas field, based on conventional logging data, a support vector machine(SVM) model is used to map the relationship between shear wave velocity and natural gamma, acoustic time difference and resistivity of shale, and then a machine learning method for shear wave velocity prediction is proposed. The model was trained...
The great popularity of smartphones and the increase in their use in everyday applications has led to sensitive information being carried in them, such as our bank account details, passwords or emails. Motivated by the limited security of traditional systems (e.g. PIN codes, secret patterns), that can be easily broken, this work focuses on the analysis of users normal interaction with touchscreens...
Market research shows that one of the most intolerable issues in the pack of cigarettes is the cigarette missing. This issue makes substantial adverse effects on a company which needs to be avoided completely. Existing research uses a weight detection method to identity packages with issues. However, the accuracy of weight detection methods is low due to instrument error and complex workshop environment...
With the development of the aviation industry and the improvement of people's living standard, more and more people choose aircraft as their way of travel, but the airline adjusts the price according to the revenue management in real time. The purpose of this paper is to design different decision-making tools from the customer's perspective, and to provide customers with the relevant information needed...
In this current age, numerous ranges of real word applications with imbalanced dataset is one of the foremost focal point of researcher's inattention. There is the enormous increment of data generation and imbalance within dataset. Processing and knowledge extraction of huge amount of imbalanced data becomes a challenge related with space and time necessities. Generally there is a list of an assortment...
There is a nonlinear relation between the blood glucose and photoplethysmography(PPG) signal. In order to estimate the blood glucose from the photoplethysmography signal, this paper presents a non-invasive blood glucose estimation using Near-Infrared spectroscopy based on the Support Vector Regression(SVR). The wavelet transform algorithm is used to remove baseline drift and smooth signals. 22 parameters,...
Uncertainty based active learning has been well studied for selecting informative samples to improve the performance of the classifier. One of the simplest strategy is that we always select samples with top largest uncertainties for a query. However, the selected samples may be very similar to each other, which results in little information added to update the classifier. In other words, we should...
In this paper, a system to aid the visually impaired by providing contextual information of the surroundings using 360° view camera combined with deep learning is proposed. The system uses a 360° view camera with a mobile device to capture surrounding scene information and provide contextual information to the user in the form of audio. The scene information from the spherical camera feed is classified...
Keyword extraction is an automated process that collects a set of terms, illustrating an overview of the document. The term is defined how the keyword identifies the core information of a particular document. Analyzing huge number of documents to find out the relevant information, keyword extraction will be the key approach. This approach will help us to understand the depth of it even before we read...
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