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Multitrack audio mixing is an essential part of music production and one of the first steps consist on processing individual stems from raw recordings. In this paper, we investigate this stage as a content-based transformation. We explore which audio features are relevant to interpret this specific process and which set of features gets modified by the mixing of stems in the most consistent way. We...
Brain computer interface applications have big importance in becoming a bridge between the human brain and devices. The studies in this area increase every day with the use of different feature extractions and classification methods In this study, classification is done by Random Forest method using Data Set III presented in BCI Competiton 2003, and it has been shown that combining the Fast Walsh...
With the increased use of smart devices, digital cameras and abundance of memory in the devices, the pictures of the same scenes have been taken several times, resulting in a number of images consisting of the same or very similar content in memory. Manually selecting the good ones is time-consuming as well as error prone. In this paper, the features of the images in the data sets were extracted and...
A mapping system based on an artificial neural network was designed, trained, and tested to map Arabic acoustic parameters to their corresponding articulatory features. The main objective of the study was to find the correlation between these two different types of features. To train and test the system, an in-house database was created for all 29 Arabic alphabets as carrier words for our intended...
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...
Classification of finger movement related to (electrocorticography) ECoG records is the main purpose of this study. Data set IV presented in BCI Competition IV was used in this study. This data set contains brain signals from three epileptic subjects and the data records consist of both ECoG and electronic glove data. ECoG segments related finger movements were extracted by means of finger movement...
This paper proposes a cheap image processing method for visual compass in the robot soccer context. An offline map is constructed by using color transition histogram features. When a feature is extracted, we calculate maximum likelihood orientation of that feature over the pre-calculated map. This instantaneous orientation information updates orientation belief with given mixing constant. We presented...
Brain computer interface technology comes at the beginning of the popular study subject for scientist that of excite all of humanity. By means of that technology it is allowed to control electronic devices for paralyzed or partial paralysis humans to make their lives easier. In literature there have been many cursor movement imagery studies based on electroencephalogram (EEG) signals. However, the...
This paper presents an approach to detects cars in omnidirectional images. We first go through the conventional method of using Haar-like features and cascaded boosting for conventional camera images. Then, to apply this method for omnidirectional cameras, we generate panoramic images from omnidirectional ones. In this way we perform car detection on a single image without generating numerous perspective...
The fields of EMG signal processing technology has been effective in the application of prosthetic control and clinical medicine or sport science. The main purpose of this study is to classify two aggressive action EMG signals which are taken from different people, according to their texture feature vectors. The physical action EMG set is derived from UCI database. The power spectral density (PSD)...
In this paper, online signature recognition is examined by using K Nearest Neighborhood (KNN) method. The signatures are collected by an Android application which can extract the dynamic and spatial information of the signatures. In this frame, a signature database is consisting of a total of 120 signatures taken from 12 different person. The purpose of this paper, is to obtain high performance with...
Eye-gaze tracking is the process of measuring the position of user's gaze. It is widely being employed in Human Computer Interaction (HCI) research area as an alternative of traditional input devices such as mouse and keyboard. In this paper, a real time vision based gaze direction detection system which can recognizes gazes in four different directions (left, right, up and bottom of the screen) and...
In this study, the experimental studies were carried out on a database containing the types of wood knot. After preprocessing on the images in the database, specific features to knot were obtained using wavelet moments feature extraction algorithm. Type description is carried out with KNN classification algorithm by selecting most distinguishing the approximation coefficients on these features. In...
This work investigates the role of canonical correlations analysis in image classification problems. Canonical correlation analysis is proposed as an alternative feature selection and reduction method for generic image classification problems. This new method is studied via various image classification problems in comparison with principal components and kernel principal components analysis. Multiple...
Feature extraction of music signals are often required in applications including; identification and classification of music files over the web or a database. The feature observations for different classes are expected to be distict, and also their computationally efficient implementations to be available. This is necessary both for offline and real time data processing. It is currently an active...
Recognition of video scenes is a challenging problem due to the unconstrained structure of the video content. Here, we propose a spatial pyramid based method for the recognition of video scenes and explore the effect of parameter optimization to the recognition accuracy. In the experiments different sampling methods, dictionary sizes, kernel methods, and pyramid levels are examined. Support Vector...
Automated cell imaging systems have been proposed for faster and more reliable analysis of biological events at the cellular level. The first step of these systems is usually cell segmentation whose success affects the other system steps. Thus, it is critical to implement robust and efficient segmentation algorithms for the design of successful systems. In the literature, the most commonly used methods...
This paper presents a pattern recognition approach which is developed for biometric identification using individual's knuckle prints. In this approach, initially palm images are segmented with active appearance models and regions of interest (knuckle prints) are extracted with using analytical processing. Afterwards, the patterns of knuckle prints are extracted by combining these regions. First, discrete...
The usage of computer vision applications such as 3D reconstruction, motion tracking and augmented reality gradually increases. The first and the most important stage of these kind of applications is esitimating the 3D scene model and motion information. We developed an easy-to-use user interface in order to use in these kind of applications. The user interface we developed, contains important functionalities...
In this work, an algorithm is introduced that classifies test images into their originated countries using composite faces generated according to different countries. Also aim to increase success rate at implementation process using three color channel (R-G-B), color feature vector and local standard deviation matrix. Algorithm used Kernel Principal Component Analysis with gauss kernel structure for...
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