Wyniki wyszukiwania dla: molecular recognition - MOST Wiedzy

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Wyniki wyszukiwania dla: molecular recognition

Wyniki wyszukiwania dla: molecular recognition

  • Vocalic Segments Classification Assisted by Mouth Motion Capture

    Visual features convey important information for automatic speech recognition (ASR), especially in noisy environment. The purpose of this study is to evaluate to what extent visual data (i.e. lip reading) can enhance recognition accuracy in the multi-modal approach. For that purpose motion capture markers were placed on speakers' faces to obtain lips tracking data during speaking. Different parameterizations strategies were tested...

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  • Investigation of educational processes with affective computing methods

    Publikacja

    This paper concerns the monitoring of educational processes with the use of new technologies for the recognition of human emotions. This paper summarizes results from three experiments, aimed at the validation of applying emotion recognition to e-learning. An analysis of the experiments’ executions provides an evaluation of the emotion elicitation methods used to monitor learners. The comparison of affect recognition algorithms...

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  • Adaptive system for recognition of sounds indicating threats to security of people and property employing parallel processing of audio data streams

    Publikacja

    - Rok 2015

    A system for recognition of threatening acoustic events employing parallel processing on a supercomputing cluster is featured. The methods for detection, parameterization and classication of acoustic events are introduced. The recognition engine is based onthreshold-based detection with adaptive threshold and Support Vector Machine classifcation. Spectral, temporal and mel-frequency descriptors are used as signal features. The...

  • Integration in Multichannel Emotion Recognition

    Publikacja

    - Rok 2018

    The paper concerns integration of results provided by automatic emotion recognition algorithms. It presents both the challenges and the approaches to solve them. Paper shows experimental results of integration. The paper might be of interest to researchers and practitioners who deal with automatic emotion recognition and use more than one solution or multichannel observation.

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  • Multiclass AdaBoost Classifier Parameter Adaptation for Pattern Recognition

    The article presents the problem of parameter value selection of the multiclass ``one against all'' approach of an AdaBoost algorithm in tasks of object recognition based on two-dimensional graphical images. AdaBoost classifier with Haar features is still used in mobile devices due to the processing speed in contrast to other methods like deep learning or SVM but its main drawback is the need to assembly the results of binary...

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  • Gesture-based computer control system

    In the paper a system for controlling computer applications by hand gestures is presented. First, selected methods used for gesture recognition are described. The system hardware and a way of controlling a computer by gestures are described. The architecture of the software along with hand gesture recognition methods and algorithms used are presented. Examples of basic and complex gestures recognized by the system are given.

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  • Automatic Classification of Polish Sign Language Words

    In the article we present the approach to automatic recognition of hand gestures using eGlove device. We present the research results of the system for detection and classification of static and dynamic words of Polish language. The results indicate the usage of eGlove allows to gain good recognition quality that additionally can be improved using additional data sources such as RGB cameras.

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  • Voice command recognition using hybrid genetic algorithm

    Publikacja

    Abstract: Speech recognition is a process of converting the acoustic signal into a set of words, whereas voice command recognition consists in the correct identification of voice commands, usually single words. Voice command recognition systems are widely used in the military, control systems, electronic devices, such as cellular phones, or by people with disabilities (e.g., for controlling a wheelchair or operating a computer...

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  • Rough Sets Applied to Mood of Music Recognition

    Publikacja

    With the growth of accessible digital music libraries over the past decade, there is a need for research into automated systems for searching, organizing and recommending music. Mood of music is considered as one of the most intuitive criteria for listeners, thus this work is focused on the emotional content of music and its automatic recognition. The research study presented in this work contains an attempt to music emotion recognition...

  • Automatic sound recognition for security purposes

    Publikacja

    - Rok 2008

    In the paper an automatic sound recognition system is presented. It forms a part of a bigger security system developed in order to monitor outdoor places for non-typical audio-visual events. The analyzed audio signal is being recorded from a microphone mounted in an outdoor place thus a non stationary noise of a significant energy is present in it. In the paper an especially designed algorithm for outdoor noise reduction is presented,...

  • Influence of accelerometer signal pre-processing and classification method on human activity recognition

    A study of data pre-processing influence on accelerometer-based human activity recognition algorithms is presented. The frequency band used to filter-out the accelerometer signals and the number of accelerometers involved were considered in terms of their influence on the recognition accuracy. In the test four methods of classification were used: support vector machine, decision trees, neural network, k-nearest neighbor.

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  • Automatic music set organizatio based on mood of music / Automatyczna organizacja bazy muzycznej na podstawie nastroju muzyki

    This work is focused on an approach based on the emotional content of music and its automatic recognition. A vector of features describing emotional content of music was proposed. Additionally, a graphical model dedicated to the subjective evaluation of mood of music was created. A series of listening tests was carried out, and results were compared with automatic mood recognition employing SOM (Self Organizing Maps) and ANN (Artificial...

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  • Examining Influence of Distance to Microphone on Accuracy of Speech Recognition

    The problem of controlling a machine by the distant-talking speaker without a necessity of handheld or body-worn equipment usage is considered. A laboratory setup is introduced for examination of performance of the developed automatic speech recognition system fed by direct and by distant speech acquired by microphones placed at three different distances from the speaker (0.5 m to 1.5 m). For feature extraction from the voice signal...

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  • Employing a biofeedback method based on hemispheric synchronization in effective learning

    In this paper an approach to build a brain computer-based hemispheric synchronization system is presented. The concept utilizes the wireless EEG signal registration and acquisition as well as advanced pre-processing methods. The influence of various filtration techniques of EOG artifacts on brain state recognition is examined. The emphasis is put on brain state recognition using band pass filtration for separation of individual...

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  • Facial emotion recognition using depth data

    Publikacja

    - Rok 2015

    In this paper an original approach is presented for facial expression and emotion recognition based only on depth channel from Microsoft Kinect sensor. The emotional user model contains nine emotions including the neutral one. The proposed recognition algorithm uses local movements detection within the face area in order to recognize actual facial expression. This approach has been validated on Facial Expressions and Emotions Database...

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  • Introduction to the special issue on machine learning in acoustics

    Publikacja
    • Z. Michalopoulou
    • P. Gerstoft
    • B. Kostek
    • M. A. Roch

    - Journal of the Acoustical Society of America - Rok 2021

    When we started our Call for Papers for a Special Issue on “Machine Learning in Acoustics” in the Journal of the Acoustical Society of America, our ambition was to invite papers in which machine learning was applied to all acoustics areas. They were listed, but not limited to, as follows: • Music and synthesis analysis • Music sentiment analysis • Music perception • Intelligent music recognition • Musical source separation • Singing...

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  • Hand gesture recognition supported by fuzzy rules and Kalman filters

    The paper presents a system based on camera and multimediaprojector enabling a user to control computer applications by dynamic hand gestures. Gesture recognition methodology based on representing hand movement trajectory by motion vectors analysed using fuzzy rule-based inference is first given. For effective hand position tracking Kalman filters are employed. The system engineered is developed using J2SE and C++/OpenCV technology....

  • Endoscopic Video Classification with the Consideration of Temporal Patterns

    The article describes a novel approach to automatic recognition and classification of diseases in endoscopic videos. Current directions of research in this field are discussed. Most presented methods focus on processing single frames and do not take into consideration the temporal relationship between continuous classifications. Existing approaches that consider the temporal structure of an incoming frame sequence are focused on...

  • Speaker Recognition Using Convolutional Neural Network with Minimal Training Data for Smart Home Solutions

    Publikacja

    - Rok 2018

    With the technology advancements in smart home sector, voice control and automation are key components that can make a real difference in people's lives. The voice recognition technology market continues to involve rapidly as almost all smart home devices are providing speaker recognition capability today. However, most of them provide cloud-based solutions or use very deep Neural Networks for speaker recognition task, which are...

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  • Robust and Efficient Machine Learning Algorithms for Visual Recognition

    Publikacja

    - Rok 2022

    In visual recognition, the task is to identify and localize all objects of interest in the input image. With the ubiquitous presence of visual data in modern days, the role of object recognition algorithms is becoming more significant than ever and ranges from autonomous driving to computer-aided diagnosis in medicine. Current models for visual recognition are dominated by models based on Convolutional Neural Networks (CNNs), which...

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  • Emotion recognition and its application in software engineering

    In this paper a novel application of multimodal emotion recognition algorithms in software engineering is described. Several application scenarios are proposed concerning program usability testing and software process improvement. Also a set of emotional states relevant in that application area is identified. The multimodal emotion recognition method that integrates video and depth channels, physiological signals and input devices...

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  • A video monitoring system using ontology-driven identification of threats

    Publikacja

    In this paper, we present a video monitoring systemthat leverages image recognition and ontological reasoningabout threats. In the solution, an image processing subsystemuses video recording of a monitored area and recognizesknown concepts in scenes. Then, a reasoning subsystem uses anontological description of security conditions and informationfrom image recognition to check if a violation of a conditionhas occurred. If a threat...

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  • FEEDB: A multimodal database of facial expressions and emotions

    Publikacja

    - Rok 2013

    In this paper a first version of a multimodal FEEDB database of facial expressions and emotions is presented. The database contains labeled RGB-D recordings of people expressing a specific set of expressions that have been recorded using Microsoft Kinect sensor. Such a database can be used for classifier training and testing in face recognition as well as in recognition of facial expressions and human emotions. Also initial experiences...

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  • Molecular geometry of phenylboronic acid

    Dane Badawcze
    open access

    Data presents molecular geometry of the ground singlet state of phenylboronic acid. The geometry was obtained via DFT calculations using Becke–Lee–Yang–Parr density functional (B3LYP) with the balanced polarized triple-zeta def2-TZVP basis set. Geometry is provided in the XYZ file format.

  • Molecular geometry of hexachlorobenzene

    Dane Badawcze
    open access

    Presented data shows molecular geometry of the ground singlet state of hexachlorobenzene and hexachlorobenzene with potassium atom in 10 angstrom distance. The geometry was obtained via MP2 and CCSD calculations using balanced polarized triple-zeta def2-TZVP basis set. Geometry is provided in the XYZ file format.

  • Dependable Integration of Medical Image Recognition Components

    Computer driven medical image recognition may support medical doctors in the diagnosis process, but requires high dependability considering potential consequences of incorrect results. The paper presentsa system that improves dependability of medical image recognition by integration of results from redundant components. The components implement alternative recognition algorithms of diseases in thefield of gastrointestinal endoscopy....

  • Towards New Mappings between Emotion Representation Models

    Publikacja

    There are several models for representing emotions in affect-aware applications, and available emotion recognition solutions provide results using diverse emotion models. As multimodal fusion is beneficial in terms of both accuracy and reliability of emotion recognition, one of the challenges is mapping between the models of affect representation. This paper addresses this issue by: proposing a procedure to elaborate new mappings,...

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  • Human emotion recognition with biosignals

    Publikacja

    - Rok 2022

    This chapter presents issues in the field of affective computing. Basic preliminary information for the recognition of emotions is given and models of emotions, various ways of evoking emotions, as well as their theoretical foundations are discussed. The particular attention is given to the use of physiological signals in recognizing emotions. This subject is outlined further below by presenting selected biosignals, their relationship...

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  • Optical recognition elements: macrocyclic imidazole chromoionophores entrapped in silica xerogel

    Publikacja

    Materials containing new chromoionophores consisting of crown residue and azole moiety as partsof macrocycles were encapsulated by the sol-gel procedure in silica xerogel matrices and proposed aschemical recognition elements especially for such metal ions as Li+, Cs+ and Cu2+. Action of these recognition elements is in principle based on changes of reflectance. The recognition elements containing 21-membered chromogenic...

  • AN ALGORITHM FOR PORTAL HYPERTENSIVE GASTROPATHY RECOGNITION ON THE ENDOSCOPIC RECORDINGS

    Publikacja

    Symptoms recognition of portal hypertensive gastropathy (PHG) can be done by analysing endoscopic recordings, but manual analysis done by physician may take a long time. This increases probability of missing some symptoms and automated methods may be applied to prevent that. In this paper a novel hybrid algorithm for recognition of early stage of portal hypertensive gastropathy is proposed. First image preprocessing is described....

  • Semantic Integration of Heterogeneous Recognition Systems

    Publikacja

    - LECTURE NOTES IN COMPUTER SCIENCE - Rok 2011

    Computer perception of real-life situations is performed using a variety of recognition techniques, including video-based computer vision, biometric systems, RFID devices and others. The proliferation of recognition modules enables development of complex systems by integration of existing components, analogously to the Service Oriented Architecture technology. In the paper, we propose a method that enables integration of information...

  • Comparison of selected off-the-shelf solutions for emotion recognition based on facial expressions

    The paper concerns accuracy of emotion recognition from facial expressions. As there are a couple of ready off-the-shelf solutions available in the market today, this study aims at practical evaluation of selected solutions in order to provide some insight into what potential buyers might expect. Two solutions were compared: FaceReader by Noldus and Xpress Engine by QuantumLab. The performed evaluation revealed that the recognition...

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  • Acceleration of decision making in sound event recognition employing supercomputing cluster

    Parallel processing of audio data streams is introduced to shorten the decision making time in hazardous sound event recognition. A supercomputing cluster environment with a framework dedicated to processing multimedia data streams in real time is used. The sound event recognition algorithms employed are based on detecting foreground events, calculating their features in short time frames, and classifying the events with Support...

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  • Endoscopic Videos Deinterlacing and On-Screen Text and Light Flashes Removal and Its Influence on Image Analysis Algorithms' Efficiency

    In this article, deinterlacing and removing on- screen text and light flashes methods on endoscopic video images are discussed. The research is intended to improve disease recognition algorithms' performance. In the article, four configurations of deinterlacing methods and another four configurations of text and flashes removal methods are described and examined. The efficiency of endoscopic video analysis algorithms is measured...

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  • Hybrid of Neural Networks and Hidden Markov Models as a modern approach to speech recognition systems

    The aim of this paper is to present a hybrid algorithm that combines the advantages ofartificial neural networks and hidden Markov models in speech recognition for control purpos-es. The scope of the paper includes review of currently used solutions, description and analysis of implementation of selected artificial neural network (NN) structures and hidden Markov mod-els (HMM). The main part of the paper consists of a description...

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  • Feature extraction in detection and recognition of graphical objects

    Publikacja

    - Rok 2022

    Detection and recognition of graphic objects in images are of great and growing importance in many areas, such as medical and industrial diagnostics, control systems in automation and robotics, or various types of security systems, including biometric security systems related to the recognition of the face or iris of the eye. In addition, there are all systems that facilitate the personal life of the blind people, visually impaired...

  • An electronic nose for quantitative determination of gas concentrations

    Publikacja

    The practical application of human nose for fragrance recognition is severely limited by the fact that our sense of smell is subjective and gets tired easily. Consequen tly, there is considerable need for an instrument that can be a substitution of the human sense of smell. Electronic nose devices from the mid 1980s are used in growing number of applications. They comprise an array of several electrochemical gas sensors...

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  • Uncertainty in emotion recognition

    Purpose–The purpose of this paper is to explore uncertainty inherent in emotion recognition technologiesand the consequences resulting from that phenomenon.Design/methodology/approach–The paper is a general overview of the concept; however, it is basedon a meta-analysis of multiple experimental and observational studies performed over the past couple of years.Findings–The mainfinding of the paper might be summarized as follows:...

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  • Using Physiological Signals for Emotion Recognition

    Publikacja

    - Rok 2013

    Recognizing user’s emotions is the promising area of research in a field of human-computer interaction. It is possible to recognize emotions using facial expression, audio signals, body poses, gestures etc. but physiological signals are very useful in this field because they are spontaneous and not controllable. In this paper a problem of using physiological signals for emotion recognition is presented. The kinds of physiological...

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  • Towards Emotion Acquisition in IT Usability Evaluation Context

    Publikacja

    - Rok 2015

    The paper concerns extension of IT usability studies with automatic analysis of the emotional state of a user. Affect recognition methods and emotion representation models are reviewed and evaluated for applicability in usability testing procedures. Accuracy of emotion recognition, susceptibility to disturbances, independence on human will and interference with usability testing procedures are...

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  • Enhanced voice user interface employing spatial filtration of signals from acoustic vector sensor

    Spatial filtration of sound is introduced to enhance speech recognition accuracy in noisy conditions. An acoustic vector sensor (AVS) is employed. The signals from the AVS probe are processed in order to attenuate the surrounding noise. As a result the signal to noise ratio is increased. An experiment is featured in which speech signals are disturbed by babble noise. The signals before and after spatial filtration are processed...

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  • Video Semantic Analysis Framework based on Run-time Production Rules - Towards Cognitive Vision

    Publikacja

    This paper proposes a service-oriented architecture for video analysis which separates object detection from event recognition. Our aim is to introduce new tools to be considered in the pathway towards Cognitive Vision as a support for classical Computer Vision techniques that have been broadly used by the scientific community. In the article, we particularly focus in solving some of the reported scalability issues found in current...

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  • Bimodal Emotion Recognition Based on Vocal and Facial Features

    Emotion recognition is a crucial aspect of human communication, with applications in fields such as psychology, education, and healthcare. Identifying emotions accurately is challenging, as people use a variety of signals to express and perceive emotions. In this study, we address the problem of multimodal emotion recognition using both audio and video signals, to develop a robust and reliable system that can recognize emotions...

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  • A Novel IoT-Perceptive Human Activity Recognition (HAR) Approach Using Multi-Head Convolutional Attention

    Publikacja

    - IEEE Internet of Things Journal - Rok 2019

    Together with fast advancement of the Internet of Things (IoT), smart healthcare applications and systems are equipped with increasingly more wearable sensors and mobile devices. These sensors are used not only to collect data, but also, and more importantly, to assist in daily activity tracking and analyzing of their users. Various human activity recognition (HAR) approaches are used to enhance such tracking. Most of the existing...

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  • Geometric Algebra Model of Distributed Representations

    Publikacja

    - Rok 2010

    Formalism based on GA is an alternative to distributed representation models developed so far-Smolensky's tensor product, Holographic Reduced Representations (HRR) and Binary Spatter Code (BSC). Convolutions are replaced by geometric products, interpretable in terms of geometry which seems to be the most natural language for visualization of higher concepts. This paper recalls the main ideas behind the GA model and investigates...

  • Multimodal English corpus for automatic speech recognition

    A multimodal corpus developed for research of speech recognition based on audio-visual data is presented. Besides usual video and sound excerpts, the prepared database contains also thermovision images and depth maps. All streams were recorded simultaneously, therefore the corpus enables to examine the importance of the information provided by different modalities. Based on the recordings, it is also possible to develop a speech...

  • The project IDENT: Multimodal biometric system for bank client identity verification

    Biometric identity verification methods are implemented inside a real banking environment comprising: dynamic handwritten signature verification, face recognition, bank cli-ent voice recognition and hand vein distribution verification. A secure communication system based on an intra-bank client-server architecture was designed for this purpose. Hitherto achieved progress within the project is reported in this paper with a focus...

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  • DevEmo—Software Developers’ Facial Expression Dataset

    The COVID-19 pandemic has increased the relevance of remote activities and digital tools for education, work, and other aspects of daily life. This reality has highlighted the need for emotion recognition technology to better understand the emotions of computer users and provide support in remote environments. Emotion recognition can play a critical role in improving the remote experience and ensuring that individuals are able...

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  • Methodology for Text Classification using Manually Created Corpora-based Sentiment Dictionary

    Publikacja

    - Rok 2018

    This paper presents the methodology of Textual Content Classification, which is based on a combination of algorithms: preliminary formation of a contextual framework for the texts in particular problem area; manual creation of the Hierarchical Sentiment Dictionary (HSD) on the basis of a topically-oriented Corpus; tonality texts recognition via using HSD for analysing the documents as a collection of topically completed fragments...

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  • Music Genre Recognition in the Rough Set-Based Environment

    Publikacja

    - Rok 2015

    The aim of this paper is to investigate music genre recognition in the rough set-based environment. Experiments involve a parameterized music data-base containing 1100 music excerpts. The database is divided into 11 classes cor-responding to music genres. Tests are conducted using the Rough Set Exploration System (RSES), a toolset for analyzing data with the use of methods based on the rough set theory. Classification effectiveness...

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