The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
In this paper we shall present recent results of two applications for monitoring using acoustical signal classification. The first case study is the problem of context awareness based on acoustic analysis for a service robot. Then we discussed the acoustic classification for wildlife intruder detection. Previous results are briefly recalled and new experimental results are also provided.
Facial recognition is a challenging problem in image processing and machine learning areas. Since widespread applications of facial recognition make it a valuable research topic, this work tries to develop some new facial recognition systems that have both high recognition accuracy and fast running speed. Efforts are made to design facial recognition systems by combining different algorithms. Comparisons...
Outlier detection is a primary step in many data mining applications. An outlier is an abnormal individual from a population, which usually leads poor accuracy in models. Medical literatures are the most reliable resources for researchers to know the progress in their research areas and latest contributions from others. Traditional keyword search retrieves all the text data that contain the keywords...
This paper describes a preliminary investigation of Voice Pathology Detection using Deep Neural Networks (DNN). We used voice recordings of sustained vowel /a/ produced at normal pitch from German corpus Saarbruecken Voice Database (SVD). This corpus contains voice recordings and electroglottograph signals of more than 2 000 speakers. The idea behind this experiment is the use of convolutional layers...
In the field of civil engineering, Ground Penetrating Radar (GPR) is the most widely used method of Non-Destructive Testing (NDT). Using supervised learning methods or signal processing methods, it is possible to analyze the sub-surface defects in pavement. In this paper, we propose to use a supervised machine learning method called Support Vector Machines (SVM) to detect the presence of debondings...
The performance of speech emotion classifiers greatly degrade when the training conditions do not match the testing conditions. This problem is observed in cross-corpora evaluations, even when the corpora are similar. The lack of generalization is particularly problematic when the emotion classifiers are used in real applications. This study addresses this problem by combining active learning (AL)...
When emotion recognition systems are used in new domains, the classification performance usually drops due to mismatches between training and testing conditions. Annotations of new data in the new domain is expensive and time demanding. Therefore, it is important to design strategies that efficiently use limited amount of new data to improve the robustness of the classification system. The use of...
We propose an image aesthetic quality assessment algorithm, which considers personal taste in addition to generally perceived preference. This problem is formulated by a combination of two different learning frameworks based on support vector machines—Support Vector Regression (SVR) and Ranking SVM (R-SVM), where SVR learns a general model based on public datasets and R-SVM adjusts the model to accommodate...
Speech impaired people are detached from the mainstream society due to the lacking of proper communication aid. Sign language is the primary means of communication for them which normal people do not understand. In order to facilitate the conversation conversion of sign language to audio is very necessary. This paper aims at conversion of sign language to speech so that disabled people have their...
Eddy Current Testing (ECT) is a fast and effective method for detecting and sizing most of the default in conducting materials. The size estimation of an unknown defect from the measurement of the impedance variations is an important technique in industrial area. This paper considers to solve this problem by the novel combination of the Least Square Support Vector Machines (LS-SVM) and Finite Element...
We propose a Convolutional Neural Network model to learn spatial footstep features end-to-end from a floor sensor system for biometric applications. Our model's generalization performance is assessed by independent validation and evaluation datasets from the largest footstep database to date, containing nearly 20,000 footstep signals from 127 users. We report footstep recognition performance as Equal...
Face spoofing can be performed in a variety of ways such as replay attack, print attack, and mask attack to deceive an automated recognition algorithm. To mitigate the effect of spoofing attempts, face anti-spoofing approaches aim to distinguish between genuine samples and spoofed samples. The focus of this paper is to detect spoofing attempts via Haralick texture features. The proposed algorithm...
Movement classification from electromyography (EMG) signals is a promising vector for improvement of human computer interaction and prosthetic control. Conventional work in this area typically makes use of expert knowledge to select a set of movements a priori and then design classifiers based around these movements. The disadvantage of this approach is that different individuals might have different...
To diagnose and classify the dysarthric speech, speech language pathologist (SLP) conducts a listening test. On the basis of the scores given by listeners the dysarthria is diagnosed and assessed. The above mentioned method is costly, time consuming and not very accurate. Unlike the traditional method, this research proposes an automatic diagnosis and assessment of dysarthria. The aim of this paper...
This paper deals with sentiment analysis in text documents, especially text valence detection. The proposed solution is based on Support Vector Machines classifier. This classifier was trained with huge amount of data and complex word combinations were analysed. For this purpose distributed learning on 112 processors was used. Datasets used for training and testing were automatically obtained from...
Texture is an important characteristic of images and hence used in a variety of computer vision applications. A group of high performing texture algorithms is based on the concept of local binary patterns (LBP) which describe the relationship of pixels to their local neighbourhoods. A rotation invariant form of this descriptor is typically employed since especially for textured surfaces rotation cannot...
This paper proposes a prediction system to make a forecast of temperature which is based on support vector machines. The system uses a database which provides information about weather parameters such as pressure, temperature, wind speed, etc. In order to adapt the input data, the present proposal has applied a pre-processing method before the prediction phases start. The best testing results have...
Playback attack detection (PAD) is essentially a binary classification task which is used to identify the authentic recordings from the playback recordings. For PAD problem, the difference of the acoustic feature between the authentic and playback recordings mainly comes from the recording channel and the ambient noise. Motivated by the excellent performance of the Gaussian Mixture Model-Universal...
Early detection of life-threatening arrhythmias such as ventricular fibrillation (VF) and rapid ventricular tachycardia (VT) is most essential for an automatic external defibrillator and remote cardiac patient monitoring. In this paper, we present a low-complexity, robust detection method for automatically detecting VT and VF events in the ECG signal. The proposed detection method consists of four...
In this work, the problem of feature extraction and image recognition in the context of RGB images and depth information (RGB-D images) is addressed. The purpose of this paper is to study and compare some popular techniques for gender recognition in order to understand how much depth data improves the quality of recognition, and identify which combination between face descriptors and learning techniques...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.