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A calibration of various microphones that have different characteristics is very difficult. This paper presents a feature extraction method as an alternative. The method provides acoustic features that are strongly robust against various characteristic transfer functions. The proposed method applies Local Binary Patterns (LBP) and Compressive Sensing (CS) which compare spectral details with spectral...
Coreference resolution plays a significant role in natural language processing systems. It is the method of figuring out all the noun phrases that refer back to the identical real world entity. Several researches have been done in noun phrase coreference resolution by using certain machine learning techniques. Our paper proposes a machine learning approach using support vector machines (SVM) towards...
Identity recognition encounters with several problems especially in feature extraction and pattern classification. Electrocardiogram (ECG) is a quasi-periodic signal which has highly discriminative characteristics in a population for subject recognition. The personal identity verification in a random population using kernel-based binary and one-class Support Vector Machines (SVMs) has been considered...
The success of machine learning (ML) algorithms depends on the quality of data given to them. If the input data contains insufficient or irrelevant features, the accuracy of machine learning algorithm decreases. Attribute selection has a key role in creation of classification models. Based on the ‘logic behind the inference’ principle in the Nyaya school of thought, this paper proposes a new method...
Social media are increasingly being used as sources in mainstream news coverage. However, since news is so rapidly updating it is very easy to fall into the trap of believing everything as truth. Spam content usually refers to the information that goes viral and skews users' views on subjects. To this end, this paper introduces a new approach for detecting spam tweets using Cost-Sensitive Classifier...
In recent years, analysis of remote sensing imagery is imperatives in the domain of environmental and climate monitoring primarily for the application of detecting and managing a natural disaster. Satellite imagery or aerial imagery is beneficial because it can widely capture the condition of the surface ground and provides a massive amount of information in a piece of satellite imagery. Since obtaining...
Radio frequency interference (RFI) is electromagnetic interference (EMI) from signals in the radio frequencies of the electromagnetic spectrum. RFI reduces the sensitivity of radio telescope and produces artefacts in the observed data. We present the result of applying machine learning techniques to detect confidently man made RFI. We confirm that not all the features selected to characterise RFI...
In this paper, we use machine learning for profiling authors of online textual media. We are interested in determining the gender and age of an author. We use two different approaches, one where the features are learned from raw data and one where features are manually extracted.We are interested in understanding how well author profiling works in the wild and therefore we have tested our models on...
FloW is a humanoid robot that is being built and developed by ER2C (Eepis Robotic Research Center). FloW is made to have human-like capabilities and one of the abilities, the robot is able to communicate with humans. Therefore, we need to build speech processing system which consists four sub-systems. There are speech-to-text system, sentence understanding system, sentence generating system and text-to-speech...
Epilepsy is defined as a collection of symptoms and clinical signs are emerging due to intermittent brain dysfunction, which occur due to loose or excessive abnormal electrical discharges of neurons in paroxysmal with various etiologies. In this article the implemented software detection of disease epilepsy, characteristics which will represent in the detection of epilepsy and not epilepsy are from...
This paper presents a novel background subtraction method that is flexible for various background scenarios. The method includes automated-directional masking (ADM) algorithm for adaptive background modeling and historical intensity pattern reference (HIPaR) algorithm for foreground segmentation. By selecting an appropriate mask in a set based on directional feature, ADM updates background smoothly...
Multimedia semantic concept detection is one of the major research topics in multimedia data analysis in recent years. Disaster information management needs the assistance of multimedia data analysis to better utilize those disasterrelated information, which has been widely shared by people through the Internet. In this paper, a Feature Affinity based Multiple Correspondence Analysis and Decision...
In this paper, we address the problem of fault detection (FD) of chemical processes using improved generalized likelihood ratio test. The improved GLRT is the method that combines the advantages of the exponentially weighted moving average (EWMA) filter with those of the GLRT method. The idea behind the developed EWMA-GLRT is to compute a new GLRT statistic that integrates current and previous data...
Security concerns increase as the technology for falsification advances and biometrics provides airtight security by identifying an individual based on the physiological and/or behavioral characteristics. Physiological hidden biometrics represented by ECG biomedical signal is highly confidential, sensitive, and hard to steal and replicate, and also hold great promise to provide a more secure biometric...
Color features extraction is one among methods widely used for mouth extraction. This relates to specific features possessed by mouth color compared to others facial components. Mouth has a strong chromatic color for red but weak for blue. Color features extraction produces colors that are used to generate a mouth map. This map is required for mouth extraction. Some previous researches on mouth extraction...
Identification of embryos in the eggs is very important first step in the process of sorting the eggs can hatch. identification system which is used to compare the input images of the object with the object database and produce eggs that are trained to see the separation between eggs that have embryos that do not have an embryo. While thresholding is one method that can be used to identify the condition...
Fully automated defect detection and classification of automobile components are crucial for solving quality and efficiency problems for automotive manufacturers, due to the rising wage, production costs and warranty claims. However, metrological deviations in form still represent unsolved problems using state-of-the-art techniques, especially for forged or casted components with complex geometry...
Real-time face recognition system process divided into three steps, feature extraction, clustering, detection, and recognition. Each step uses a different method that is Local Binary Pattern (LBP), Agglomerative Hierarchical Clustering (AHC) and Euclidean Distance. Content Based Image Retrieval (CBIR), an image searching techniques based on image feature, is implemented as the searching method. Based...
Car Recognition is a part of Intelligent Transportation System. This research proposes the manufacture of ITS-based system to identify car model from Its frontal image using Binary Robust Invariant Scalable method. The BRISK method is used to detect image keypoint, and it uses Hamming Distance for keypoint matching. As for matching error, this research depends on RANSAC. BRISK method excellence lies...
This research proposes a reliable machine learning based computational solution for human detection. The proposed model is specifically applicable for illumination-variant natural scenes in big data video frames. In order to solve the illumination variation problem, a new feature set is formed by extracting features using histogram of gradients (HoG) and linear phase quantization (LPQ) techniques,...
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