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Wyniki wyszukiwania dla: IMAGE SEGMENTATION, DEEP LEARNING, AUTOMATED BEHAVIOR RECOGNITION, RODENT SOCIAL BEHAVIOR
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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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Book Review
PublikacjaActing over the last three decades as an Editor and Associate Editor for a number of international journals in the general area of cybernetics and AI, as well as a Chair and Co-Chair of numerous conferences in this field, I have had the exciting opportunity to closely witness and to be actively engaged in the stimulating research area of machine learning and its important augmentation with deep learning techniques and technologies. From...
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Smart Approach for Glioma Segmentation in Magnetic Resonance Imaging using Modified Convolutional Network Architecture (U-NET)
PublikacjaSegmentation of a brain tumor from magnetic resonance multimodal images is a challenging task in the field of medical imaging. The vast diversity in potential target regions, appearance and multifarious intensity threshold levels of various tumor types are few of the major factors that affect segmentation results. An accurate diagnosis and its treatment demand strict delineation of the tumor affected tissues. Herein, we focus on...
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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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Revising Entrepreneurial Orientation Construct in Social Enterprise
PublikacjaEntrepreneurial behavior and entrepreneurial orientation (EO) have received significant scholarly attention in entrepreneurship and management research, but mainly in the commercial context. However, some attempts discussing such behavior and EO among non-profit organizations, but limited in the social enterprise context. The literature argues that EO is higher in such contexts (Zahra, Gedajlovic, Neubaum & Shulman, 2009; Lumpkin,...
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AN ALGORITHM FOR PORTAL HYPERTENSIVE GASTROPATHY RECOGNITION ON THE ENDOSCOPIC RECORDINGS
PublikacjaSymptoms 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....
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WYKORZYSTANIE SIECI NEURONOWYCH DO SYNTEZY MOWY WYRAŻAJĄCEJ EMOCJE
PublikacjaW 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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Fully Automated AI-powered Contactless Cough Detection based on Pixel Value Dynamics Occurring within Facial Regions
PublikacjaIncreased interest in non-contact evaluation of the health state has led to higher expectations for delivering automated and reliable solutions that can be conveniently used during daily activities. Although some solutions for cough detection exist, they suffer from a series of limitations. Some of them rely on gesture or body pose recognition, which might not be possible in cases of occlusions, closer camera distances or impediments...
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AUTOMATIC LEARNING OF STRATEGY AND RULES IN CARD GAMES USING IMAGE FROM CAMERA
PublikacjaBelow work tries to answer a question: if it is possible to replace real human with computer system in social games. As a subject for experiments, card games were chosen, because they require a lot of player interaction (playing and taking cards), while their rules are easy to present in form of clear list of statements. Such a system, should allow real players to play without constant worrying about guiding or helping computer...
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Towards discovering human urban activity—tactics of human spatial behavior
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THE ROLE OF INFERENCE IN MOBILE MEDICAL APPLICATION DESIGN
PublikacjaIn the early 21st century, artificial intelligence began to be used to process medical information. However, before this happened, predictive models used in healthcare could only consider a limited number of variables, and only in properly structured and organised medical data. Today, advanced tools based on machine learning techniques - which, using artificial neural networks, can explore extremely complex relationships - and...
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Semantic segmentation training using imperfect annotations and loss masking
PublikacjaOne of the most significant factors affecting supervised neural network training is the precision of the annotations. Also, in a case of expert group, the problem of inconsistent data annotations is an integral part of real-world supervised learning processes, well-known to researchers. One practical example is a weak ground truth delineation for medical image segmentation. In this paper, we have developed a new method of accurate...
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Instructor Presence in Video Lectures: Preliminary Findings From an Online Experiment
PublikacjaMotivation. Despite the widespread use of video lectures in online and blended learning environments, there is still debate whether the presence of an instructor in the video helps or hinders learning. According to social agency theory, seeing the instructor makes learners believe that s/he is personally teaching them, which leads to deeper cognitive processing and, in turn, better learning outcomes. Conversely, according to cognitive...
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Attention-Based Deep Learning System for Classification of Breast Lesions—Multimodal, Weakly Supervised Approach
PublikacjaBreast cancer is the most frequent female cancer, with a considerable disease burden and high mortality. Early diagnosis with screening mammography might be facilitated by automated systems supported by deep learning artificial intelligence. We propose a model based on a weakly supervised Clustering-constrained Attention Multiple Instance Learning (CLAM) classifier able to train under data scarcity effectively. We used a private...
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Impact of Visual Image Quality on Lymphocyte Detection Using YOLOv5 and RetinaNet Algorithms
PublikacjaLymphocytes, a type of leukocytes, play a vital role in the immune system. The precise quantification, spatial arrangement and phenotypic characterization of lymphocytes within haematological or histopathological images can serve as a diagnostic indicator of a particular lesion. Artificial neural networks, employed for the detection of lymphocytes, not only can provide support to the work of histopathologists but also enable better...
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DevEmo—Software Developers’ Facial Expression Dataset
PublikacjaThe 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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Technology-Enhanced Environmental Learning: Co-design of Educational Mobile Application Case
PublikacjaThe process of co-creating an educational mobile application to support environmentally friendly behavior is presented in this paper. The research material consisted of quantitative data collected on the application during the first testing phase by early adopters. The results suggest that the most frequently used features of the app were related to transport and educational activities. While women tended to split their time between...
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Selected Technical Issues of Deep Neural Networks for Image Classification Purposes
PublikacjaIn recent years, deep learning and especially Deep Neural Networks (DNN) have obtained amazing performance on a variety of problems, in particular in classification or pattern recognition. Among many kinds of DNNs, the Convolutional Neural Networks (CNN) are most commonly used. However, due to their complexity, there are many problems related but not limited to optimizing network parameters, avoiding overfitting and ensuring good...
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Multiclass AdaBoost Classifier Parameter Adaptation for Pattern Recognition
PublikacjaThe 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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CERTIFICATION SYSTEM AS A TOOL FOR IMPROVING THE SAFETY AND SUSTAINABILITY OF SCHOOL-RELATED TRAVELS
PublikacjaDespite the well-established physical, social, emotional, cognitive, and spatial benefits of active and autonomous school commuting of children and adolescents', many are driven by car. Pilot surveys and field research held in 2019 in 10 Gdansk primary schools confirmed this trend. The article presents a certification system for schools, commissioned by the City of Gdańsk, which is an element of a systemic solution shaping patterns...
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Training of Deep Learning Models Using Synthetic Datasets
PublikacjaIn order to solve increasingly complex problems, the complexity of Deep Neural Networks also needs to be constantly increased, and therefore training such networks requires more and more data. Unfortunately, obtaining such massive real world training data to optimize neural networks parameters is a challenging and time-consuming task. To solve this problem, we propose an easy-touse and general approach to training deep learning...
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Predicting emotion from color present in images and video excerpts by machine learning
PublikacjaThis work aims at predicting emotion based on the colors present in images and video excerpts using a machine-learning approach. The purpose of this paper is threefold: (a) to develop a machine-learning algorithm that classifies emotions based on the color present in an image, (b) to select the best-performing algorithm from the first phase and apply it to film excerpt emotion analysis based on colors, (c) to design an online survey...
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Identification of Emotional States Using Phantom Miro M310 Camera
PublikacjaThe purpose of this paper is to present the possibilities associated with the use of remote sensing methods in identifying human emotional states, and to present the results of the research conducted by the authors in this field. The studies presented involved the use of advanced image analysis to identify areas on the human face that change their activity along with emotional expression. Most of the research carried out in laboratories...
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Decision-Making Models of the Human-Operator as an Element of the Socio-Technical Systems
PublikacjaThe authors of the chapter proved that the fundamental intellectual processes, which lie on the basis of decision-making behavior of the human-operator, could be identified on the bases on the analogies with the devices (elements). The basic intellectual processes of the Rational decision-making models can be adequately identified by the transient processes of the PID-controller; the intellectual processes of the Bounded Rationality...
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Adversarial attack algorithm for traffic sign recognition
PublikacjaDeep learning suffers from the threat of adversarial attacks, and its defense methods have become a research hotspot. In all applications of deep learning, intelligent driving is an important and promising one, facing serious threat of adversarial attack in the meanwhile. To address the adversarial attack, this paper takes the traffic sign recognition as a typical object, for it is the core function of intelligent driving. Considering...
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Rediscovering Automatic Detection of Stuttering and Its Subclasses through Machine Learning—The Impact of Changing Deep Model Architecture and Amount of Data in the Training Set
PublikacjaThis work deals with automatically detecting stuttering and its subclasses. An effective classification of stuttering along with its subclasses could find wide application in determining the severity of stuttering by speech therapists, preliminary patient diagnosis, and enabling communication with the previously mentioned voice assistants. The first part of this work provides an overview of examples of classical and deep learning...
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imPlatelet classifier: image‐converted RNA biomarker profiles enable blood‐based cancer diagnostics
PublikacjaLiquid biopsies offer a minimally invasive sample collection, outperforming traditional biopsies employed for cancer evaluation. The widely used material is blood, which is the source of tumor-educated platelets. Here, we developed the imPlatelet classifier, which converts RNA-sequenced platelet data into images in which each pixel corresponds to the expression level of a certain gene. Biological knowledge from the Kyoto Encyclopedia...
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Discovering interactions between applications with log analysis
PublikacjaApplication logs record the behavior of a system during its runtime and their analysis can provide useful information. In this article, we propose a method of automated log analysis to discover interactions taking place between applications in an enterprise. We believe that such an automated approach can greatly support enterprise architects in building an up-to-date view of a governed system in a modern, fast-paced development...
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Age, frequency of volunteering, and Present-Hedonistic time perspective predict donating items to people in need, but not money to combat COVID-19 during lock-down
PublikacjaRestrictions due to COVID-19 necessitated staying at home, but in some cases, encouraged charitable behavior, e.g., donating items to people in need (e.g., clothes, food), or money to support combatting COVID-19. Drawing on the previous findings regarding helping during disastrous situations and roles of time perspective in helping behaviors, the study tested the predictive value of age, gender, previous volunteering, altruistic...
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Melanoma skin cancer detection using mask-RCNN with modified GRU model
PublikacjaIntroduction: Melanoma Skin Cancer (MSC) is a type of cancer in the human body; therefore, early disease diagnosis is essential for reducing the mortality rate. However, dermoscopic image analysis poses challenges due to factors such as color illumination, light reflections, and the varying sizes and shapes of lesions. To overcome these challenges, an automated framework is proposed in this manuscript. Methods: Initially, dermoscopic...
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Robust Object Detection with Multi-input Multi-output Faster R-CNN
PublikacjaRecent years have seen impressive progress in visual recognition on many benchmarks, however, generalization to the out-of-distribution setting remains a significant challenge. A state-of-the-art method for robust visual recognition is model ensembling. However, recently it was shown that similarly competitive results could be achieved with a much smaller cost, by using multi-input multi-output architecture (MIMO). In this work,...
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Robust Object Detection with Multi-input Multi-output Faster R-CNN
PublikacjaRecent years have seen impressive progress in visual recognition on many benchmarks, however, generalization to the out-of-distribution setting remains a significant challenge. A state-of-the-art method for robust visual recognition is model ensembling. However, recently it was shown that similarly competitive results could be achieved with a much smaller cost, by using multi-input multi-output architecture (MIMO). In this work,...
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Controlling computer by lip gestures employing neural network
PublikacjaResults of experiments regarding lip gesture recognition with an artificial neural network are discussed. The neural network module forms the core element of a multimodal human-computer interface called LipMouse. This solution allows a user to work on a computer using lip movements and gestures. A user face is detected in a video stream from a standard web camera using a cascade of boosted classifiers working with Haar-like features....
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Nonlocal Vibration of Carbon/Boron-Nitride Nano-hetero-structure in Thermal and Magnetic Fields by means of Nonlinear Finite Element Method
PublikacjaHybrid nanotubes composed of carbon and boron-nitride nanotubes have manifested as innovative building blocks to exploit the exceptional features of both structures simultaneously. On the other hand, by mixing with other types of materials, the fabrication of relatively large nanotubes would be feasible in the case of macroscale applications. In the current article, a nonlinear finite element formulation is employed to deal with...
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Optimized Deep Learning Model for Flood Detection Using Satellite Images
PublikacjaThe increasing amount of rain produces a number of issues in Kerala, particularly in urban regions where the drainage system is frequently unable to handle a significant amount of water in such a short duration. Meanwhile, standard flood detection results are inaccurate for complex phenomena and cannot handle enormous quantities of data. In order to overcome those drawbacks and enhance the outcomes of conventional flood detection...
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Speaker Recognition Using Convolutional Neural Network with Minimal Training Data for Smart Home Solutions
PublikacjaWith 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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THE INFLUENCE OF INTERPERSONAL MOTIVATION ON POLISH CONSUMERS’ ONLINE BRAND-RELATED ACTIVITY
PublikacjaThe development of social media has a substantial impact on the surge of social engagement of Internet users. It is particularly prominent in the domain of content creation and content sharing. Such communication may contain various references to different products brands and companies. Internet users may refer to them explicitly or brands may be present in the background only. Therefore, it is pivotal for managers and researchers...
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Building the Learning Environment for Sustainable Development: a Co-creation approach
PublikacjaEducation for sustainable development supports the improvement of knowledge, skills, attitudes and behaviors related to global challenges such as climate change, global warming and environmental degradation, among others. It is increasingly taking place through projects based on information and communication technologies. The effectiveness of the actions taken depends not only on the quality of the project activities or the...
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Performance Analysis of the OpenCL Environment on Mobile Platforms
PublikacjaToday’s smartphones have more and more features that so far were only assigned to personal computers. Every year these devices are composed of better and more efficient components. Everything indicates that modern smartphones are replacing ordinary computers in various activities. High computing power is required for tasks such as image processing, speech recognition and object detection. This paper analyses the performance of...
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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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Explainable AI for Inspecting Adversarial Attacks on Deep Neural Networks
PublikacjaDeep Neural Networks (DNN) are state of the art algorithms for image classification. Although significant achievements and perspectives, deep neural networks and accompanying learning algorithms have some important challenges to tackle. However, it appears that it is relatively easy to attack and fool with well-designed input samples called adversarial examples. Adversarial perturba-tions are unnoticeable for humans. Such attacks...
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Exploring perceptions of pro environmental educational mobile applications based on semantic field analysis
PublikacjaThe paper aims to identify multidimensional perceptions of mobile apps by their users. Special attention has been paid to pro-environmental educational apps. Semantic field analysis and measurement of emotional temperatures were performed to achieve this goal. Transcripts from seven focus group interviews were used as research material. The results indicate that functionality based on a reward or benefit system reinforces environmentally...
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Znaczenie płci w procesie zakupu marek własnych sieci handlowych – analiza wielogrupowa
PublikacjaThe purpose of the article is to analyze the differences in the behavior of men and women in the process of purchasing store brands (SBs). Using an established conceptual model, we intended to identify differences, depending on gender of buyers, in the size of the effects of store image and brand price-image on perceived risk and subsequently on store brand purchase intention. A total of 652 respondents participated in the study....
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Tome-lapse X-ray tomography imaging of flow patterns in versatile silo model
PublikacjaThe paper introduces a new versatile silo model that was especially designed for in situ X-ray tomography studies of silo discharge for various flow conditions, namely concentric and eccentric. The presented work focuses on organic granular materials where low fraction of short-grain white rice is mixed with spheroidal sorghum particles. The high-quality tomography images combined with adequate image processing strategy allows...
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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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Evaluating Accuracy of Respiratory Rate Estimation from Super Resolved Thermal Imagery
PublikacjaNon-contact estimation of Respiratory Rate (RR) has revolutionized the process of establishing the measurement by surpassing some issues related to attaching sensors to a body, e.g. epidermal stripping, skin disruption and pain. In this study, we perform further experiments with image processing-based RR estimation by using various image enhancement algorithms. Specifically, we employ Super Resolution (SR) Deep Learning (DL) network...
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Medical Image Dataset Annotation Service (MIDAS)
PublikacjaMIDAS (Medical Image Dataset Annotation Service) is a custom-tailored tool for creating and managing datasets either for deep learning, as well as machine learning or any form of statistical research. The aim of the project is to provide one-fit-all platform for creating medical image datasets that could easily blend in hospital's workflow. In our work, we focus on the importance of medical data anonimization, discussing the...
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JamesBot - an intelligent agent playing StarCraft II
PublikacjaThe most popular method for optimizing a certain strategy based on a reward is Reinforcement Learning (RL). Lately, a big challenge for this technique are computer games such as StarCraft II which is a real-time strategy game, created by Blizzard. The main idea of this game is to fight between agents and control objects on the battlefield in order to defeat the enemy. This work concerns creating an autonomous bot using reinforced...
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Automatic analysis of the aggressive behavior of laboratory animals using thermal video processing
PublikacjaThe bite detection is very important but difficult element of the social interaction analysis. Standard observation methods like human observer or a camcorder of visible light frequencies fail in this case. However, it is possible to discern cooler spots on the rodent's body that appear after body contact with another individual, and vanish after short time. These spots are assumed to be a saliva trace left on fur after bite. In...
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Validation of a virtual test environment for C2X communication under radio jamming conditions
PublikacjaIn this paper, we propose a novel car-2-x communication security testing methodology in the physical layer of wireless systems. The approach is dedicated to automated testing of autonomous vehicles and it is essential for such complex systems operation, especially with regard to safety and security issues. It is based on scenario-driven testing in virtual and real test environments created from collected or simulated data. The...