Results (41)
Search Parameters:
Keyword: Feature extractionEEG Feature Extraction based on Fast Fourier Transform and Wavelet Analysis for Classification of Mental Stress Levels using Machine Learning
Mental stress assessment remains riddled with biases caused by subjective reports and individual differences across societal backgrounds. To objectively determine the presence or absence of mental stress, there is a need to move away from the traditional subjective methods of self-report questionnaires and interviews. Previously, it has been evidence that EEG Oscillations can discriminate mental…
Read MoreNumerical Analysis for Feature Extraction and Evaluation of 3D Sickness
Artificial intelligence (AI) systems have been applied not only to numerical simulations of the economical sequences but also to the bio-signal, for instance, the statokinesigrams (SKGs). According to the nonlinear analysis of the bio-signal, we have considered that the motion process of the body sway is more random than that of the other bio-signal. In…
Read MoreObserver-Based Method of Feature Extraction for the Fault Detection of Permanent Magnet Synchronous Motors
This paper presents a new observer-based method which deals with the extraction of amplitude of characteristic frequencies for the fault diagnosis in permanent magnet synchronous motors (PMSM). First, a pilot survey is made to investigate the typical harmonics in the line currents of PMSM. Second, an appropriate structure of observer is formulated with the input…
Read MoreEye Feature Extraction with Calibration Model using Viola-Jones and Neural Network Algorithms
This paper presents the setup of eye tracking calibration methodology and the preliminary test results of the training model from the eye tracking data. Eye tracking requires good accuracy from the calibration process of the human eyes feature extraction from facial region. Viola-Jones algorithm is applied for this purpose by using Haar Basic feature filters…
Read MoreMulti Biometric Thermal Face Recognition Using FWT and LDA Feature Extraction Methods with RBM DBN and FFNN Classifier Algorithms
Person recognition using thermal imaging, multi-biometric traits, with groups of feature filters and classifiers, is the subject of this paper. These were used to tackle the problems of biometric systems, such as a change in illumination and spoof attacks. Using a combination of, hard and soft-biometric, attributes in thermal facial images. The hard-biometric trait, of…
Read MoreApplication of Feature Extraction for Breast Cancer using One Order Statistic, GLCM, GLRLM, and GLDM
The increasing number of breast cancer in recent years has attracted numerous researchers’ attention. Several techniques of Computer Aided Diagnosis System have been proposed as alternative solutions to diagnose breast cancer. The flaw of simply using the naked eye to see the differences between normal and with cancer mammogram images makes the texture analysis play…
Read MoreA Machine Learning Framework Using Distinctive Feature Extraction for Hand Gesture Recognition
There are more than 7billion people in the world where there are around 500 million people in the world who are denied from normal lifestyle due to physical and mental issue. It is completely fair to say that every person deserves to enjoy a normal lifestyle. While physically and mentally challenged people find suitable way…
Read MoreDomain Independent Feature Extraction using Rule Based Approach
Sentiment analysis is one of the most popular information extraction tasks both from business and research prospective. From the standpoint of research, sentiment analysis relies on the methods developed for natural language processing and information extraction. One of the key aspects of it is the opinion word lexicon. Product’s feature from online reviews is an…
Read MoreAutomated Extraction of Heavyweight and Lightweight Models of Urban Features from LiDAR Point Clouds by Specialized Web-Software
3D city modeling may be considered as one of the key applications, that are provided by the Automated Feature Extraction (AFE) techniques from LiDAR data. The authors attempt to prove that with growing availability of LiDAR surveying methods the resulted 3D city models become the most significant modeled features for any urban environment. Our paper…
Read MoreConvolutional Neural Network Based on HOG Feature for Bird Species Detection and Classification
This work is concerned with the detection and classification of birds that have applications like monitoring extinct and migrated birds. Recent computer vision algorithms can precise this kind of task but still there are some dominant issues like low light, very little differences between subspecies of birds, etc are to be studied. As Convolution Neural…
Read MoreFeature Extractors Evaluation Based V-SLAM for Autonomous Vehicles
Visual Simultaneous Localization and Mapping known as V-SLAM, is an essential task for autonomous vehicles. It can be carried out using several sensors, in particular with on board cameras. To locate a vehicle, SLAM algorithms are based on two main tasks. The first task (front-end kernel) is intended to process images in order to provide…
Read MoreMultiscale Texture Analysis and Color Coherence Vector Based Feature Descriptor for Multispectral Image Retrieval
Content Based Image Retrieval (CBIR) for remote sensing image data is a tedious process due to high resolution and complexity of image interpretation. Development of feature extraction technique is a major portion to represent the image content in an optimal way. In this paper, we propose a feature descriptor which combines the color coherent pixel…
Read MoreFeature Selection for Musical Genre Classification Using a Genetic Algorithm
Music genre classification is an important multimedia research domain, including aspects of music piece representation, distances between genres, and categorization of music databases. The objective of this study was to develop a model for automatic classification of musical genres from audio data by using features from low-level time and frequency domains. These features can highlight…
Read MoreAutomatic Stitching of Medical Images Using Feature Based Approach
Image stitching is a process of creating a panoramic image by combining multiple images that have overlapping regions of the same scene. It is a challenging topic in image processing, multimedia, and medical applications. The proposed system can be applied in medical applications for scoliosis operations and other long limb operations. The problem of the…
Read MoreSelf-Organizing Map based Feature Learning in Bio-Signal Processing
Feature extraction is playing a significant role in bio-signal processing. Feature identification and selection has two approaches. The standard method is engineering handcraft which is based on user experience and application area. While the other approach is feature learning that based on making the system identify and select the best features suit the application. The…
Read MoreAn Ensemble of Voting- based Deep Learning Models with Regularization Functions for Sleep Stage Classification
Sleep stage performs a vital role in people’s daily lives in the detection of sleep-related diseases. Conventional automated sleep stage classifier models are not efficient due to the complexity linked to the design of mathematical models and extraction of hand-engineering features. Further, quick oscillations amongst sleep stages frequently lead to indistinct feature extraction, which might…
Read MoreAn Alternative Approach for Thai Automatic Speech Recognition Based on the CNN-based Keyword Spotting with Real-World Application
An automatic speech recognition (ASR) is a key technology for preventing an ongoing global coronavirus epidemic. Due to the limited corpus database and the morphological diversity of the Thai language, Thai speech recognition is still difficult. In this research, the automatic speech recognition model was built differently from the traditional Thai NLP systems by using…
Read MorePerformance Evaluation of Convolutional Neural Networks (CNNs) And VGG on Real Time Face Recognition System
Face Recognition (FR) is considered as a heavily studied topic in computer vision field. The capability to automatically identify and authenticate human’s faces using real-time images is an important aspect in surveillance, security, and other related domains. There are separate applications that help in identifying individuals at specific locations which help in detecting intruders. The…
Read MoreA Model for the Application of Automatic Speech Recognition for Generating Lesson Summaries
Automatic Speech Recognition (ASR) technology has the potential to improve the learning experience of students in the classroom. This article addresses some of the key theoretical areas identified in the pursuit of implementing a speech recognition system, capable of lesson summary generation in the educational setting. The article discusses: some of the applica- tions of…
Read MoreTexture Based Image Retrieval Using Semivariogram and Various Distance Measures
In a content-based image retrieval system(CBIR) feature classification,identification, and ex- traction play an important role. The retrieval of images using a single feature is a challenging task in CBIR systems. The high retrieval rates are reported based on combining multiple features, multiple algorithms and preprocessing steps, feature classification, and segmentation because the image retrieval are…
Read MoreMultiple Machine Learning Algorithms Comparison for Modulation Type Classification Based on Instantaneous Values of the Time Domain Signal and Time Series Statistics Derived from Wavelet Transform
Modulation type classification is a part of waveform estimation required to employ spectrum sharing scenarios like dynamic spectrum access that allow more efficient spectrum utilization. In this work multiple classification features, feature extraction, and classification algorithms for modulation type classification have been studied and compared in terms of classification speed and accuracy to suggest the…
Read MoreSH-CNN: Shearlet Convolutional Neural Network for Gender Classification
Gender detection and age estimation become an active research area and a very important field today, wish has been widely used in various applications including them: biometrics, social network, Targeted advertising, access control, human-computer interaction, electronic customer, etc. The need to further improve the recognition or classification rate keeps increasing day after day. In this…
Read MoreHuman Emotion Recognition Based on EEG Signal Using Fast Fourier Transform and K-Nearest Neighbor
Human emotional states can transform naturally and are recognizable through facial expressions, voices, or body movements, influenced by received stimuli. However, the articulation of emotions is not practicable by every individual, even when feelings of joy, sadness, or otherwise are experienced. Biomedically, emotions affect brain wave activities, as the continuously functioning brain cells communicate through…
Read MoreDense Deep Neural Network Architecture for Keystroke Dynamics Authentication in Mobile Phone
The ever-growing technology in mobile smartphones has enabled users to store sensitive and private information; as a result, it required the need for an improved security system. Previous approaches heavily relied on shallow machine learning algorithms that require feature extraction which is time consuming, laborious and can cause, resulting in poor authentication. In this paper,…
Read MoreInteractive Virtual Rehabilitation for Aphasic Arabic-Speaking Patients
Objective: Individuals with aphasia often experience significant problems in their daily lives and social participation. Technologies that address speech and language disorders deficit in merging between therapist’s major role and reinforcing the training between sessions at home. It also lacks the Arabic language attention; however, current systems are typically expensive and lack amusement. Moreover, cumulative…
Read More
