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Wyniki wyszukiwania dla: REPRESENTATION LEARNING
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Fusion-based Representation Learning Model for Multimode User-generated Social Network Content
PublikacjaAs mobile networks and APPs are developed, user-generated content (UGC), which includes multi-source heterogeneous data like user reviews, tags, scores, images, and videos, has become an essential basis for improving the quality of personalized services. Due to the multi-source heterogeneous nature of the data, big data fusion offers both promise and drawbacks. With the rise of mobile networks and applications, UGC, which includes...
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Integrating Experience-Based Knowledge Representation and Machine Learning for Efficient Virtual Engineering Object Performance
PublikacjaMachine learning and Artificial Intelligence have grown significant attention from industry and academia during the past decade. The key reason behind interest is such technologies capabilities to revolutionize human life since they seamlessly integrate classical networks, networked objects and people to create more efficient environments. In this paper, the Knowledge Representation technique of Set of Experience...
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Model-free and Model-based Reinforcement Learning, the Intersection of Learning and Planning
PublikacjaMy doctoral dissertation is intended as the compound of four publications considering: structure and randomness in planning and reinforcement learning, continuous control with ensemble deep deterministic policy gradients, toddler-inspired active representation learning, and large-scale deep reinforcement learning costs.
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Comparative Analysis of Text Representation Methods Using Classification
PublikacjaIn our work, we review and empirically evaluate five different raw methods of text representation that allow automatic processing of Wikipedia articles. The main contribution of the article—evaluation of approaches to text representation for machine learning tasks—indicates that the text representation is fundamental for achieving good categorization results. The analysis of the representation methods creates a baseline that cannot...
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Speech Analytics Based on Machine Learning
PublikacjaIn this chapter, the process of speech data preparation for machine learning is discussed in detail. Examples of speech analytics methods applied to phonemes and allophones are shown. Further, an approach to automatic phoneme recognition involving optimized parametrization and a classifier belonging to machine learning algorithms is discussed. Feature vectors are built on the basis of descriptors coming from the music information...
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Affective computing and affective learning – methods, tools and prospects
PublikacjaEvery teacher knows that interest, active participation and motivation are important factors in the learning process. At the same time e-learning environments almost always address only the cognitive aspects of education. This paper provides a brief review of methods used for affect recognition, representation and processing as well as investigates how these methods may be used to address affective aspect of e-education. The paper...
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Student model representation for pedagogical virtual mentors
PublikacjaThe paper concerns technological aspects of virtual mentors construction, especially concentrating on the student model representation. The article distinguishes several types of information that is gathered by the pedagogical agents and other educational platforms, including student knowledge model, student progress tracking, interaction process patterns and learner preferences. A set of technologies used for the student model...
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MP3vec: A Reusable Machine-Constructed Feature Representation for Protein Sequences
Publikacja—Machine Learning (ML) methods have been used with varying degrees of success on protein prediction tasks, with two inherent limitations. First, prediction performance often depends upon the features extracted from the proteins. Second, experimental data may be insufficient to construct reliable ML models. Here we introduce MP3vec, a transferable representation for protein sequences that is designed to be used specifically for sequence-to-sequence...
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When Neural Networks Meet Decisional DNA: A Promising New Perspective for Knowledge Representation and Sharing
PublikacjaABSTRACT In this article, we introduce a novel concept combining neural network technology and Decisional DNA for knowledge representation and sharing. Instead of using traditional machine learning and knowledge discovery methods, this approach explores the way of knowledge extraction through deep learning processes based on a domain’s past decisional events captured by Decisional DNA. We compare our approach with kNN (k-nearest...
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Path-based methods on categorical structures for conceptual representation of wikipedia articles
PublikacjaMachine learning algorithms applied to text categorization mostly employ the Bag of Words (BoW) representation to describe the content of the documents. This method has been successfully used in many applications, but it is known to have several limitations. One way of improving text representation is usage of Wikipedia as the lexical knowledge base – an approach that has already shown promising results in many research studies....
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Learning and memory processes in autonomous agents using an intelligent system of decision-making
PublikacjaThis paper analyzes functions and structures of the memory that is an indispensable part of an Intelligent System of Decision-making (ISD), developed as a universal engine for autonomous robotics. A simplified way of processing and coding information in human cognitive processes is modelled and adopted for the use in autonomous systems. Based on such a knowledge structure, an artificial model of reality representation and a model...
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Learning and memory processes in autonomous agents using an intelligent system of decision-making
PublikacjaThis paper analyzes functions and structures of the memory that is an indispensable part of an Intelligent System of Decision-making (ISD), developed as a universal engine for autonomous robotics. A simplified way of processing and coding information in human cognitive processes is modelled and adopted for the use in autonomous systems. Based on such a knowledge structure, an artificial model of reality representation and a model...
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Detecting Lombard Speech Using Deep Learning Approach
PublikacjaRobust Lombard speech-in-noise detecting is challenging. This study proposes a strategy to detect Lombard speech using a machine learning approach for applications such as public address systems that work in near real time. The paper starts with the background concerning the Lombard effect. Then, assumptions of the work performed for Lombard speech detection are outlined. The framework proposed combines convolutional neural networks...
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Machine Learning Applied to Aspirated and Non-Aspirated Allophone Classification—An Approach Based on Audio "Fingerprinting"
PublikacjaThe purpose of this study is to involve both Convolutional Neural Networks and a typical learning algorithm in the allophone classification process. A list of words including aspirated and non-aspirated allophones pronounced by native and non-native English speakers is recorded and then edited and analyzed. Allophones extracted from English speakers’ recordings are presented in the form of two-dimensional spectrogram images and...
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Visual Content Representation for Cognitive Systems: Towards Augmented Intelligence
PublikacjaCognitive Vision Systems have gained significant attention from academia and industry during the past few decades. One of the main reasons behind this interest is the potential of such technologies to revolutionize human life since they intend to work robustly under complex visual scenes (which environmental conditions may vary), adapting to a comprehensive range of unforeseen changes, and exhibiting prospective behavior. The combination...
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Affective Learning Manifesto – 10 Years Later
PublikacjaIn 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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Towards New Mappings between Emotion Representation Models
PublikacjaThere 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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Application of Intelligent Conversational Agents in E-learing Environments
PublikacjaThe paper concerns intelligent tutoring systems and concentrates on apliaction of virtual mentors in distance learning environments. Different educational agent types are described. The prototype of an agent developed at Gdansk University of Technology is also presented, as well as its internal representation and construction. Benefits of virtual mentors applied in distance learning are also pointed out.
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Adapt Your Teacher: Improving Knowledge Distillation for Exemplar-free Continual Learning
PublikacjaIn this work, we investigate exemplar-free class incremental learning (CIL) with knowledge distillation (KD) as a regularization strategy, aiming to prevent forgetting. KDbased methods are successfully used in CIL, but they often struggle to regularize the model without access to exemplars of the training data from previous tasks. Our analysis reveals that this issue originates from substantial representation shifts in the teacher...
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Investigating Feature Spaces for Isolated Word Recognition
PublikacjaThe study addresses the issues related to the appropriateness of a two-dimensional representation of speech signal for speech recognition tasks based on deep learning techniques. The approach combines Convolutional Neural Networks (CNNs) and time-frequency signal representation converted to the investigated feature spaces. In particular, waveforms and fractal dimension features of the signal were chosen for the time domain, and...
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Graph Representation Integrating Signals for Emotion Recognition and Analysis
PublikacjaData reusability is an important feature of current research, just in every field of science. Modern research in Affective Computing, often rely on datasets containing experiments-originated data such as biosignals, video clips, or images. Moreover, conducting experiments with a vast number of participants to build datasets for Affective Computing research is time-consuming and expensive. Therefore, it is extremely important to...
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Experience-Oriented Knowledge Management for Internet of Things
PublikacjaIn this paper, we propose a novel approach for knowledge management in Internet of Things. By utilizing Decisional DNA and deep learning technologies, our approach enables Internet of Things of experiential knowledge discovery, representation, reuse, and sharing among each other. Rather than using traditional machine learning and knowledge discovery methods, this approach focuses on capturing domain’s decisional events via Decisional...
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Active Annotation in Evaluating the Credibility of Web-Based Medical Information: Guidelines for Creating Training Data Sets for Machine Learning
PublikacjaMethods Results Discussion References Abbreviations Copyright Abstract Background: The spread of false medical information on the web is rapidly accelerating. Establishing the credibility of web-based medical information has become a pressing necessity. Machine learning offers a solution that, when properly deployed, can be an effective tool in fighting medical misinformation on the web. Objective: The aim of this study is to...
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Investigating Feature Spaces for Isolated Word Recognition
PublikacjaMuch attention is given by researchers to the speech processing task in automatic speech recognition (ASR) over the past decades. The study addresses the issue related to the investigation of the appropriateness of a two-dimensional representation of speech feature spaces for speech recognition tasks based on deep learning techniques. The approach combines Convolutional Neural Networks (CNNs) and timefrequency signal representation...
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Toward Intelligent Vehicle Intrusion Detection Using the Neural Knowledge DNA
PublikacjaIn this paper, we propose a novel intrusion detection approach using past driving experience and the neural knowledge DNA for in-vehicle information system security. The neural knowledge DNA is a novel knowledge representation method designed to support discovering, storing, reusing, improving, and sharing knowledge among machines and computing systems. We examine our approach for classifying malicious vehicle control commands...
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Adding Intelligence to Cars Using the Neural Knowledge DNA
PublikacjaIn this paper we propose a Neural Knowledge DNA based framework that is capable of learning from the car’s daily operation. The Neural Knowledge DNA is a novel knowledge representation and reasoning approach designed to support discovering, storing, reusing, improving, and sharing knowledge among machines and computing devices. We examine our framework for drivers' classification based on their driving behaviour. The experimental...
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Smart Knowledge Engineering for Cognitive Systems: A Brief Overview
PublikacjaCognition in computer sciences refers to the ability of a system to learn at scale, reason with purpose, and naturally interact with humans and other smart systems, such as humans do. To enhance intelligence, as well as to introduce cognitive functions into machines, recent studies have brought humans into the loop, turning the system into a human–AI hybrid. To effectively integrate and manipulate hybrid knowledge, suitable technologies...
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Playback detection using machine learning with spectrogram features approach
PublikacjaThis paper presents 2D image processing approach to playback detection in automatic speaker verification (ASV) systems using spectrograms as speech signal representation. Three feature extraction and classification methods: histograms of oriented gradients (HOG) with support vector machines (SVM), HAAR wavelets with AdaBoost classifier and deep convolutional neural networks (CNN) were compared on different data partitions in respect...
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Toward Intelligent Recommendations Using the Neural Knowledge DNA
PublikacjaIn this paper we propose a novel recommendation approach using past news click data and the Neural Knowledge DNA (NK-DNA). The Neural Knowledge DNA is a novel knowledge representation method designed to support discovering, storing, reusing, improving, and sharing knowledge among machines and computing systems. We examine our approach for news recommendation tasks on the MIND benchmark dataset. By taking advantages of NK-DNA, deep...
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Experience-Oriented Intelligence for Internet of Things
PublikacjaThe Internet of Things (IoT) has gained significant attention from industry as well as academia during the past decade. The main reason behind this interest is the capabilities of the IoT for seamlessly integrating classical networks and networked objects, and hence allows people to create an intelligent environment based on this powerful integration. However, how to extract useful information from data produced by IoT and facilitate...
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Decisional DNA for modeling and reuse of experiential clinical assessments in breast cancer diagnosis and treatment
PublikacjaClinical Decision Support Systems (CDSS) are active knowledge resources that use patient data to generate case specific advice. The fast pace of change of clinical knowledge imposes to CDSS the continuous update of the domain knowledge and decision criteria. Traditional approaches require costly tedious manual maintenance of the CDSS knowledge bases and repositories. Often, such an effort cannot be assumed by medical teams, hence...
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An Automated Method for Biometric Handwritten Signature Authentication Employing Neural Networks
PublikacjaHandwriting biometrics applications in e-Security and e-Health are addressed in the course of the conducted research. An automated graphomotor analysis method for the dynamic electronic representation of the handwritten signature authentication was researched. The developed algorithms are based on dynamic analysis of electronically handwritten signatures employing neural networks. The signatures were acquired with the use of the...
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A new multi-process collaborative architecture for time series classification
PublikacjaTime series classification (TSC) is the problem of categorizing time series data by using machine learning techniques. Its applications vary from cybersecurity and health care to remote sensing and human activity recognition. In this paper, we propose a novel multi-process collaborative architecture for TSC. The propositioned method amalgamates multi-head convolutional neural networks and capsule mechanism. In addition to the discovery...
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Analysis-by-synthesis paradigm evolved into a new concept
PublikacjaThis work aims at showing how the well-known analysis-by-synthesis paradigm has recently been evolved into a new concept. However, in contrast to the original idea stating that the created sound should not fail to pass the foolproof synthesis test, the recent development is a consequence of the need to create new data. Deep learning models are greedy algorithms requiring a vast amount of data that, in addition, should be correctly...
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Applying Decisional DNA to Internet of Things: The Concept and Initial Case Study
PublikacjaIn this article, we present a novel approach utilizing Decisional DNA to help the Internet of Things capture decisional events and reuse them for decision making in future operations. The Decisional DNA is a domain-independent, standard and flexible knowledge representation structure that allows its domains to acquire, store, and share experiential knowledge and formal decision events in an explicit way. We apply this approach...
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Application of autoencoder to traffic noise analysis
PublikacjaThe aim of an autoencoder neural network is to transform the input data into a lower-dimensional code and then to reconstruct the output from this code representation. Applications of autoencoders to classifying sound events in the road traffic have not been found in the literature. The presented research aims to determine whether such an unsupervised learning method may be used for deploying classification algorithms applied to...
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Detection of Lexical Stress Errors in Non-Native (L2) English with Data Augmentation and Attention
PublikacjaThis paper describes two novel complementary techniques that improve the detection of lexical stress errors in non-native (L2) English speech: attention-based feature extraction and data augmentation based on Neural Text-To-Speech (TTS). In a classical approach, audio features are usually extracted from fixed regions of speech such as the syllable nucleus. We propose an attention-based deep learning model that automatically de...
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Optymalizacja zasobów chmury obliczeniowej z wykorzystaniem inteligentnych agentów w zdalnym nauczaniu
PublikacjaRozprawa dotyczy optymalizacji zasobów chmury obliczeniowej, w której zastosowano inteligentne agenty w zdalnym nauczaniu. Zagadnienie jest istotne w edukacji, gdzie wykorzystuje się nowoczesne technologie, takie jak Internet Rzeczy, rozszerzoną i wirtualną rzeczywistość oraz deep learning w środowisku chmury obliczeniowej. Zagadnienie jest istotne również w sytuacji, gdy pandemia wymusza stosowanie zdalnego nauczania na dużą skalę...
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Vehicle detector training with labels derived from background subtraction algorithms in video surveillance
PublikacjaVehicle detection in video from a miniature station- ary closed-circuit television (CCTV) camera is discussed in the paper. The camera provides one of components of the intelligent road sign developed in the project concerning the traffic control with the use of autonomous devices being developed. Modern Convolutional Neural Network (CNN) based detectors need big data input, usually demanding their manual labeling. In the presented...
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Identification of the Contamination Source Location in the Drinking Water Distribution System Based on the Neural Network Classifier
PublikacjaThe contamination ingression to the Water Distribution System (WDS) may have a major impact on the drinking water consumers health. In the case of the WDS contamination the data from the water quality sensors may be efficiently used for the appropriate disaster management. In this paper the methodology based on the Learning Vector Quantization (LVQ) neural network classifier for the identification of the contamination source location...
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Influence of Thermal Imagery Resolution on Accuracy of Deep Learning based Face Recognition
PublikacjaHuman-system interactions frequently require a retrieval of the key context information about the user and the environment. Image processing techniques have been widely applied in this area, providing details about recognized objects, people and actions. Considering remote diagnostics solutions, e.g. non-contact vital signs estimation and smart home monitoring systems that utilize person’s identity, security is a very important factor....
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Graphical interface adaption for children to explain astronomy proportions and distances
PublikacjaMobile Science Center is a Polish project that seeks to bring astronomy knowledge to wider social groups through various applications. In its development it is necessary to design a graphical interface that explains a concept that is difficult to assimilate such as spatial proportions and distances. This paper develops a framework to create graphical representations that explain this learning to the target audience of children....
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Ontology-based text convolution neural network (TextCNN) for prediction of construction accidents
PublikacjaThe construction industry suffers from workplace accidents, including injuries and fatalities, which represent a significant economic and social burden for employers, workers, and society as a whole.The existing research on construction accidents heavily relies on expert evaluations,which often suffer from issues such as low efficiency, insufficient intelligence, and subjectivity.However, expert opinions provided in construction...
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Application of artificial intelligence into/for control of flexible manufacturing cell
PublikacjaThe application of artificial intelligence in technological processes control is usually limited. One problem is how to respond to changes in the environment of manufacturing system. A way to overcome the above shortcoming is to use fuzzy logic for representation of the inexact information. In this paper fundamentals of artificial intelligence and fuzzy logic are introduced from a theoretical point of view. Still more the fuzzy...
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Vehicle detector training with minimal supervision
PublikacjaRecently many efficient object detectors based on convolutional neural networks (CNN) have been developed and they achieved impressive performance on many computer vision tasks. However, in order to achieve practical results, CNNs require really large annotated datasets for training. While many such databases are available, many of them can only be used for research purposes. Also some problems exist where such datasets are not...
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Special forms of echo visual representation in an ahead looking sonar.
PublikacjaThe paper discusses ways to organise visual representation in a multi-beam ahead looking sonars whose function is to detect objects on the bottom and in pelagic zones. Forms of visual representation are shown and illustrated on the basic screen (panoramic representation and setting, alarms) and on the auxiliary screen (type A, B and special). Special forms of visual representation are mainly used in detecting objects in difficult...
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Geometric analogue of holographic reduced representation
PublikacjaHolographic reduced representations (HRRs) are distributed representations of cognitive structuresbased on superpositions of convolution-bound n-tuples. Restricting HRRs to n-tuples consisting of 1,one reinterprets the variable binding as a representation of the additive group of binary n-tupleswith addition modulo 2. Since convolutions are not defined for vectors, the HRRs cannot be directlyassociated with geometric structures....
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Computational Model of Time for Stiff Hybrid Systems Applied to Control Synthesis
PublikacjaComputational representation.
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Set of Experience and Decisional DNA: Experience-Based Knowledge Structures
PublikacjaThis chapter presents a description of Set of Experience Knowledge Structure (SOEKS) and Decisional DNA (DDNA), argumentation for a knowledge representation, composition, configuration and metrics. SOEKS is a combination of filtered and amalgamated information obtained from formal decision events. It facilitates effective explicit representation of decisional experience taken from different technologies. SOEKS comprises variables,...
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Virtual Engineering Objects: Effective Way of Knowledge Representation and Decision Making
PublikacjaThis paper presents a knowledge representation case study by constructing Decisional DNA of engineering objects. Decisional DNA, as a knowledge representation structure not only offers great possibilities on gathering explicit knowledge of formal decision events but also it is a powerful tool for decision-making process. The concept of Virtual engineering Object (VEO), which is a knowledge and experience representation of engineering...