Search results for: COLOR GRADING, MUSIC AND EMOTION RECOGNITION, PERCEPTION, MACHINE LEARNING.
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A Computationally Efficient Model for Predicting Successful Memory Encoding Using Machine-Learning-based EEG Channel Selection
PublicationComputational cost is an important consideration for memory encoding prediction models that use data from dozens of implanted electrodes. We propose a method to reduce computational expense by selecting a subset of all the electrodes to build the prediction model. The electrodes were selected based on their likelihood of measuring brain activity useful for predicting memory encoding better than chance (in terms of AUC). A logistic...
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Development of advanced machine learning for prognostic analysis of drying parameters for banana slices using indirect solar dryer
PublicationIn this study, eXtreme Gradient Boosting (XGBoost) and Light Gradient Boosting (LightGBM) algorithms were used to model-predict the drying characteristics of banana slices with an indirect solar drier. The relationships between independent variables (temperature, moisture, product type, water flow rate, and mass of product) and dependent variables (energy consumption and size reduction) were established. For energy consumption,...
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AffecTube — Chrome extension for YouTube video affective annotations
PublicationThe shortage of emotion-annotated video datasets suitable for training and validating machine learning models for facial expression-based emotion recognition stems primarily from the significant effort and cost required for manual annotation. In this paper, we present AffecTube as a comprehensive solution that leverages crowdsourcing to annotate videos directly on the YouTube platform, resulting in ready-to-use emotion-annotated...
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Machine Learning- and Artificial Intelligence-Derived Prediction for Home Smart Energy Systems with PV Installation and Battery Energy Storage
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Machine Learning Algorithm-Based Tool and Digital Framework for Substituting Daylight Simulations In Early- Stage Architectural Design Evaluation
PublicationThe aim of this paper is to examine the new method of obtaining the simulation-based results using backpropagation of errors artificial neural networks. The primary motivation to conduct the research was to determine an alternative, more efficient and less timeconsuming method which would serve to achieve the results of daylight simulations. Three daylight metrics: Daylight Factor, Daylight Autonomy and Daylight Glare Probability have...
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Personalized prediction of the secondary oocytes number after ovarian stimulation: A machine learning model based on clinical and genetic data
PublicationControlled ovarian stimulation is tailored to the patient based on clinical parameters but estimating the number of retrieved metaphase II (MII) oocytes is a challenge. Here, we have developed a model that takes advantage of the patient’s genetic and clinical characteristics simultaneously for predicting the stimulation outcome. Sequence variants in reproduction-related genes identified by next-generation sequencing were matched...
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Analysis of pedestrian activity before and during COVID-19 lockdown, using webcam time-lapse from Cracow and machine learning
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Determinants of anxiety levels among young males in a threat of experiencing military conflict–Applying a machine-learning algorithm in a psychosociological study
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Machine-learning-based precise cost-efficient NO2 sensor calibration by means of time series matching and global data pre-processing
PublicationAir pollution remains a considerable contemporary challenge affecting life quality, the environment, and economic well-being. It encompasses an array of pollutants—gases, particulate matter, biological molecules—emanating from sources such as vehicle emissions, industrial activities, agriculture, and natural occurrences. Nitrogen dioxide (NO2), a harmful gas, is particularly abundant in densely populated urban areas. Given its...
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Statistical Data Pre-Processing and Time Series Incorporation for High-Efficacy Calibration of Low-Cost NO2 Sensor Using Machine Learning
PublicationAir pollution stands as a significant modern-day challenge impacting life quality, the environment, and the economy. It comprises various pollutants like gases, particulate matter, biological molecules, and more, stemming from sources such as vehicle emissions, industrial operations, agriculture, and natural events. Nitrogen dioxide (NO2), among these harmful gases, is notably prevalent in densely populated urban regions. Given...
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Investigation of educational processes with affective computing methods
PublicationThis 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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Agnieszka Landowska dr hab. inż.
PeopleAgnieszka Landowska works for Gdansk University of Technology, FETI, Department of Software Engineering. Her research concentrates on usability, accessibility and technology adoption, as well as affective computing methods. She initiated Emotions in HCI Research Group and conducts resarch on User eXperiene evaluation of applications and other technologies.
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The influence of sound track on the viewer’s emotions and correction of the color in the film
PublicationThe article presents the aspects of the final selection of colors in film production based on the emotions caused by the soundtrack of the film. First, the processing of colors, contrast, saturation and white balance of shots in the film was presented. The definition of color grading is also described, i.e. the color changes in the film's views. In the second part of the article, the soundtracks of the film were analyzed, in particular...
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Michał Grochowski dr hab. inż.
PeopleProfessor and a Head of the Department of Intelligent Control and Decision Support Systems at Gdansk University of Technology (GUT). He is also a Member of the Board of the Digital Technologies Center of GUT. He received his M.Sc. degree in Control Engineering in 2000 from the Electrical and Control Engineering Faculty at the GUT. In 2004 he received a Ph.D. degree in Automatic Control and Robotics from this...
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Music Mood Visualization Using Self-Organizing Maps
PublicationDue to an increasing amount of music being made available in digital form in the Internet, an automatic organization of music is sought. The paper presents an approach to graphical representation of mood of songs based on Self-Organizing Maps. Parameters describing mood of music are proposed and calculated and then analyzed employing correlation with mood dimensions based on the Multidimensional Scaling. A map is created in which...
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JOURNAL OF MACHINE LEARNING RESEARCH
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Julita Wasilczuk dr hab.
PeopleBorn on 5th of April, 1965 in Gdansk. In 1987-1991 studied the economics of transport, at the University of Gdansk. At 1993 she started to work at the Faculty of Management and Economics. In 1997 received a PhD at the faculty, in 2006 habilitation at the Faculty of Management, University of Gdansk. Since 2009 Associate Professor at Gdansk University of Technology. In 2010-2012 Associate Professor of Humanistic High School at Gdansk. The...
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Affective Learning Manifesto – 10 Years Later
PublicationIn 2004 a group of affective computing researchers proclaimed a manifesto of affective learning that outlined the prospects and white spots of research at that time. Ten years passed by and affective computing developed many methods and tools for tracking human emotional states as well as models for affective systems construction. There are multiple examples of affective methods applications in Intelligent Tutoring Systems (ITS)....
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DevEmo—Software Developers’ Facial Expression Dataset
PublicationThe 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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Sound engineering as our commitment to its creators in Poland
PublicationSound engineering is an interdisciplinary and rapidly expanding domain. It covers many aspects, such as sound perception, studio and sound mastering technology, music information retrieval including content-based search systems and automatic music transcription frameworks, sound synthesis, sound restoration, electroacoustics, and other ones constituting multimedia technology. Moreover, machine learning methods applied to the topics...
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Towards New Mappings between Emotion Representation Models
PublicationThere 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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Color transformation methods for dichromats
PublicationColor blindness is a serious perception problem. Suffering individuals cannot understand messages, which are carrying by many images, especially those, distributed by WWW. In this paper we are proposing three image processing methods to enhance image recognition and understanding by persons with dichromacy. Color difference image is introduced to represent color perception dissimilarity. Two color transformation methods are presented....
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Listening to Live Music: Life beyond Music Recommendation Systems
PublicationThis paper presents first a short review on music recommendation systems based on social collaborative filtering. A dictionary of terms related to music recommendation systems, such as music information retrieval (MIR), Query-by-Example (QBE), Query-by-Category (QBC), music content, music annotating, music tagging, bridging the semantic gap in music domain, etc. is introduced. Bases of music recommender systems are shortly presented,...
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Asian Conference on Machine Learning
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International Conference on Machine Learning
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Music information retrieval—The impact of technology, crowdsourcing, big data, and the cloud in art.
PublicationThe exponential growth of computer processing power, cloud data storage, and crowdsourcing model of gathering data bring new possibilities to music information retrieval (mir) field. Mir is no longer music content retrieval only; the area also comprises the discovery of expressing feelings and emotions contained in music, incorporating other than hearing modalities for helping this issue, users’ profiling, merging music with social...
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WYKORZYSTANIE SIECI NEURONOWYCH DO SYNTEZY MOWY WYRAŻAJĄCEJ EMOCJE
PublicationW niniejszym artykule przedstawiono analizę rozwiązań do rozpoznawania emocji opartych na mowie i możliwości ich wykorzystania w syntezie mowy z emocjami, wykorzystując do tego celu sieci neuronowe. Przedstawiono aktualne rozwiązania dotyczące rozpoznawania emocji w mowie i metod syntezy mowy za pomocą sieci neuronowych. Obecnie obserwuje się znaczny wzrost zainteresowania i wykorzystania uczenia głębokiego w aplikacjach związanych...
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Source code - AI models (MLM1-5 - series I-III - QNM opt)
Open Research DataSource code - AI models (MLM1-5 - series I-III - QNM opt) for the paper "Computational Complexity and Its Influence on Concrete Compressive Strength Prediction Capabilities of Machine Learning Models for Concrete Mix Design Support" accepted for publication.
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Relationship between album cover design and music genres.
PublicationThe aim of the study is to find out whether there exists a relationship between typographic, compositional and coloristic elements of the music album cover design and music contained in the album. The research study involves basic statistical analysis of the manually extracted data coming from the worldwide album covers. The samples represent 34 different music genres, coming from nine countries from around the world. There are...
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International Conference on Machine Learning and Cybernetics
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International Conference on Machine Learning and Applications
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Automatic music set organizatio based on mood of music / Automatyczna organizacja bazy muzycznej na podstawie nastroju muzyki
PublicationThis 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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THE INFLUENCE OF QUESTION SET ON STUDENT QUIZ RESULTS
PublicationThe advent of e-Learning tools allowing for automated online test grading will probably increase the frequency of using tests in technical education. The same tools may provide for measures of test question quality. By purposely crafting question sets, test grading may serve different goals. The paper contains examples and test study with score histograms.
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Adrian Kastrau mgr inż.
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Color Processing for Color-Blind Individuals Using Smart Glasses
PublicationIn this paper we investigated image processing methods for color-blind individuals. In particular we experimentally verified color naming procedure, generation of maps with color perception differences for average observers and for dichromats, and two color transformation methods. In experiments 7 mobile devices were used: 3 smart glasses and 4 smartphones. User studies were performed with 38 average observers and 9 dichromats....
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Towards Emotion Acquisition in IT Usability Evaluation Context
PublicationThe 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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Musical Instrument Separation Applied to Music Genre Classification . Separacja instrumentów muzycznych w zastosowaniu do rozpoznawania gatunków muzycznych
PublicationThis paper outlines first issues related to music genre classification and a short description of algorithms used for musical instrument separation. Also, the paper presents proposed optimization of the feature vectors used for music genre recognition. Then, the ability of decision algorithms to properly recognize music genres is discussed based on two databases. In addition, results are cited for another database with regard to...
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Identification of Emotions Based on Human Facial Expressions Using a Color-Space Approach
PublicationHCI technology improves human-computer interaction. Such communication can be carried out with the use of emotions that are visible on the human face since birth. In this paper the Emotion system for detecting and recognizing facial expressions, developed in the MSc work, is presented. The system recognizes emotion from webcam video in real time. It is based on color segmentation and morphological operations. The system uses a...
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From Linear Classifier to Convolutional Neural Network for Hand Pose Recognition
PublicationRecently gathered image datasets and the new capabilities of high-performance computing systems have allowed developing new artificial neural network models and training algorithms. Using the new machine learning models, computer vision tasks can be accomplished based on the raw values of image pixels instead of specific features. The principle of operation of deep neural networks resembles more and more what we believe to be happening...
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Automatic recognition of males and females among web browser users based on behavioural patterns of peripherals usage
PublicationPurpose The purpose of this paper is to answer the question whether it is possible to recognise the gender of a web browser user on the basis of keystroke dynamics and mouse movements. Design/methodology/approach An experiment was organised in order to track mouse and keyboard usage using a special web browser plug-in. After collecting the data, a number of parameters describing the users’ keystrokes, mouse movements and clicks...
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Bożena Kostek prof. dr hab. inż.
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Deep Learning
PublicationDeep learning (DL) is a rising star of machine learning (ML) and artificial intelligence (AI) domains. Until 2006, many researchers had attempted to build deep neural networks (DNN), but most of them failed. In 2006, it was proven that deep neural networks are one of the most crucial inventions for the 21st century. Nowadays, DNN are being used as a key technology for many different domains: self-driven vehicles, smart cities,...
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Podstawy uczenia maszynowego AI
e-Learning CoursesPodstawy uczenia maszynowego. Machine Learning fundamentals.
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Comparative analysis of spectral and cepstral feature extraction techniques for phoneme modelling
PublicationPhoneme parameter extraction framework based on spectral and cepstral parameters is proposed. Using this framework, the phoneme signal is divided into frames and Hamming window is used. The performances are evaluated for recognition of Lithuanian vowel and semivowel phonemes. Different feature sets without noise as well as at different level of noise are considered. Two classical machine learning methods (Naive Bayes and Support...
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Guido: a musical score recognition system
PublicationThis paper presents an optical music recognition system Guido that can automatically recognize the main musical symbols of music scores that were scanned or taken by a digital camera. The application is based on object model of musical notation and uses linguistic approach for symbol interpretation and error correction. The system offers musical editor with a partially automatic error correction.
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The Neural Knowledge DNA Based Smart Internet of Things
PublicationABSTRACT The Internet of Things (IoT) has gained significant attention from industry as well as academia during the past decade. Smartness, however, remains a substantial challenge for IoT applications. Recent advances in networked sensor technologies, computing, and machine learning have made it possible for building new smart IoT applications. In this paper, we propose a novel approach: the Neural Knowledge DNA based Smart Internet...
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Report of the ISMIS 2011 Contest : Music Information Retrieval
PublicationThis report presents an overview of the data mining contestorganized in conjunction with the 19th International Symposiumon Methodologies for Intelligent Systems (ISMIS 2011), in days betweenJan 10 and Mar 21, 2011, on TunedIT competition platform. The contestconsisted of two independent tasks, both related to music information retrieval:recognition of music genres and recognition of instruments, for agiven music sample represented...
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Voice command recognition using hybrid genetic algorithm
PublicationAbstract: 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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Emotion monitoring system for drivers
PublicationThis article describes a new approach to the issue of building a driver monitoring system. Actual systems focus, for example, on tracking eyelid and eyebrow movements that result from fatigue. We propose a different approach based on monitoring the state of emotions. Such a system assumes that by using the emotion model based on our own concept, referred to as the reverse Plutchik’s paraboloid of emotions, the recognition of emotions...
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Design Elements of Affect Aware Video Games
PublicationIn this paper issues of design and development process of affect-aware video games are presented. Several important design aspects of such games are pointed out. A concept of a middleware framework is proposed that separates the development of affect-aware video games from emotion recognition algorithms and support from input sensors. Finally, two prototype affect-aware video games are presented that conform to the presented architecture...