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In order to reduce the false matching rate and matching time, an improved algorithm based on RANSAC-SIFT was proposed. The feature points were extracted by SIFT algorithm firstly. Then most of the mismatching points were eliminated according to the constraints that matching distances tend to be consistent. Finally the remaining points were regarded as pre matching points for achieve fine matching...
Conventionally small area topographic detail plan is produced using land survey techniques. Various method of modern topographical detail plan however required more cost to speed up the data acquisition process for large data and high accuracy. The recent development in commercial grade Unmanned Aerial Vehicle (UAV) has the potential to be used as a data capture equipment with low cost. In this study,...
Sentiment analysis deals with identifying polarity orientation embedded in users' comments and reviews. It aims at discriminating positive reviews from negative ones. Sentiment is related to culture and language morphology. In this paper, we investigate the effects of language morphology on sentiment analysis in reviews written in the Arabic language. In particular, we investigate, in details, how...
Feature learning plays a crucial role in the successful human action recognition. There has been a number of approaches extracting action features from depth information and 3D skeletal data. However, either the skeleton information or the depth map is not accurate for feature learning unless complex descriptors are carefully designed and embedded. In this paper, we first propose a data sparsification...
Currently, There are many E-commerce websites around the internet world. These E-commerce websites can be categorized into many types which one of them is C2C (Customer to Customer) websites such as eBay and Amazon. The main objective of C2C websites is an online market place that everyone can buy or sell anything at any time. Since, there are a lot of products in the E-commerce websites and each...
Gait recognition, a manner to measure a person walk, has emerged as a new biometric technology due to the imperative need for efficient security infrastructure. There are several uniqueness associated with this technology: non-invasive, hard to conceal, and perceivable at a low-resolution. Unfortunately, gait exhibits large variations due to changes in view angles, clothing, footwear, carrying conditions,...
In this paper, an epileptic seizure event detection algorithm utilizing five features namely singular values, total average power, delta band average power, variance and mean, is proposed. Using CHB-MIT Scalp EEG Database, the calculations of the features are performed over a sliding window of one second. The algorithm was evaluated in terms of accuracy, sensitivity, specificity and failure rate....
The current benchmark speech-based depression detection techniques rely on acoustic speech parameters collected from large sets of representative speech recordings. This study for the first time investigates depression detection based on the higher order influence model (HOIM) coefficients and emotional transition parameters derived from a relatively small set of conversational speech recordings representing...
Sentiment feature selection (SFS) refers to the task of automatically identifying whether a feature contributes to sentiment classification. Most existing researches do not make a distinction between sentiment classification and topical text classification. Actually, the former commonly depends more on features conveying sentiments while the latter depends on features with strong class distinguish-ability...
Ultra WideBand(UWB) Impulse Radio (IR) has huge advantages in target identification for its broad band, good concealment and strong ability to penetrate obstacles. We apply the UWB-IR technology theory in target identification under the foliage environment. It is different from the traditional radar and wireless sensor network (WSN), for it combines forward communication and target identification...
As one of the largest Social Media in providing public data every day, Twitter has attracted the attention of researcher to investigate, in order to mine public opinion, which is known as Sentiment Analysis. Consequently, many techniques and studies related to Sentiment Analysis over Twitter have been proposed in recent years. However, there is no study that discuss about sentence pattern of positive/negative...
This paper performs a comparative analysis of QRS and Cardioid Graph Based ECG Biometric Recognition incorporating Physiological variability. Data was acquired from 30 subjects, where each subject performed six types of physical activities namely walking, going upstairs, going downstairs, natural gait, lying with position changed and resting while watching TV. Then from the signals of these physiological...
Emotion play an important role at several activities in the present world. Human decision making, cognitive process and interaction between human & machine all the activities depends on human emotions. Facial expression, musical activities and several approaches used to find the human emotions. In this paper EEG is used to find the accurate emotion. Emotion classification is the huge task. Classification...
Cardiovascular disease (CVD) is the leading cause of death throughout the world. Since electrocardiogram-reports (ECG) have a great CVD predicting potential, the demand for their real-time analysis is high. Although algorithms are present to perform analysis, most countries still use analogue acquisition systems that can only output a printed trace. It is necessary to extract the signal from these...
Developing efficient and usable brain-computer interfaces (BCIs) requires well-designed trade-off between accuracy and computational time. This paper presents a very fast and accurate method to classify asynchronous brain signals from a multi-class mental tasks dataset using time-domain features. Five different statistical time-domain features were extracted to characterize various properties of three...
Word level Script and language identification is a process of separating the script and language of each word present in a printed or handwritten multi-script document. It is an essential part of a multi-lingual Optical Character Recognizer (OCR). Most of the OCRs are solely designed for a single script. So it can't convert a document which is written in more than one script. This paper explained...
This paper presents an evaluation of characteristic frequency features in healthy and diseased ECG via k-NN classifier. Initially, a total of 264 segment samples are obtained for healthy, bundle branch blocks, dysrhythmia cardiomyopathy conditions from the PTB Diagnostic ECG database. The signal is preprocessed to obtain the power spectral density. The characteristic frequency for each segment sample...
This document describes the analysis of Electroenchaplogram (EEG) or brain signals using computational tool (LabVIEW) to interpret human thought such as moving forward, backward, turn right, turn left and to stop. This study is conducted to assist the disable people to communicate with external environment. The EEG signals are captured using wireless EEG amplifier while the subject in relax conditioin...
This paper presents a method of detecting and segmenting regions of interest (ROIs) of the thermal image of electrical installations. These regions are very important in diagnosing the thermal condition of electrical equipment. Due to the nature of thermal imaging, segmentation with the conventional approach will make inaccurate ROI detection, especially when qualitative approach is considered in...
Good performance of pedestrian detection in an automatic driving system is a necessary task. Many pedestrian detection algorithm use Histogram Oriented Gradient (HOG) for feature extraction and Support Vector Machine (SVM) for classification. Some papers use additional features with HOG, such as Local Binary Pattern (HOG-LBP), to improve the performance. Neural Network and Extreme Learning Machine...
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