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- Publikacje 957 wyników po odfiltrowaniu
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Wyniki wyszukiwania dla: SELF-SUPERVISED LEARNING, VEHICLE DETECTION, CNN, WEAKLY-SUPERVISED LEARNING
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Deep Learning-based Recalibration of the CUETO and EORTC Prediction Tools for Recurrence and Progression of Non–muscle-invasive Bladder Cancer
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Machine Learning Algorithm-Based Tool and Digital Framework for Substituting Daylight Simulations In Early- Stage Architectural Design Evaluation
PublikacjaThe 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
PublikacjaControlled 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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From Linear Classifier to Convolutional Neural Network for Hand Pose Recognition
PublikacjaRecently 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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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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Weighted Ensemble with one-class Classification and Over-sampling and Instance selection (WECOI): An approach for learning from imbalanced data streams
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E-learning przez Internet w szkolnictwie wyższym. Doświadczenia Szkoły Głównej Handlowej w Warszawie i Politechniki Gdańskiej.
PublikacjaOpisano cztery podstawowe rodzaje e-learningu, przedstawiono strukturę funkcjonalną systemów zarządzania nauczaniem na odległość i zarządzania treścią nauczania (ang. LMS, LCMS) oraz zaprezentowano doświadczenia Szkoły Głównej Handlowej w Warszawie i Politechniki Gdańskiej w nauczaniu na odległość.
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An automated learning model for twitter sentiment analysis using Ranger AdaBelief optimizer based Bidirectional Long Short Term Memory
PublikacjaSentiment analysis is an automated approach which is utilized in process of analysing textual data to describe public opinion. The sentiment analysis has major role in creating impact in the day-to-day life of individuals. However, a precise interpretation of text still relies as a major concern in classifying sentiment. So, this research introduced Bidirectional Long Short Term Memory with Ranger AdaBelief Optimizer (Bi-LSTM RAO)...
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The Learning Organization
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DEEP CONVOLUTIONAL NEURAL NETWORKS AS A DECISION SUPPORT TOOL IN MEDICAL PROBLEMS – MALIGNANT MELANOMA CASE STUDY
PublikacjaThe paper presents utilization of one of the latest tool from the group of Machine learning techniques, namely Deep Convolutional Neural Networks (CNN), in process of decision making in selected medical problems. After the survey of the most successful applications of CNN in solving medical problems, the paper focuses on the very difficult problem of automatic analyses of the skin lesions. The authors propose the CNN structure...
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Socioeconomic and gender inequalities in home learning during the COVID-19 pandemic: examining the roles of the home environment, parent supervision, and educational provisions
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Statistical Data Pre-Processing and Time Series Incorporation for High-Efficacy Calibration of Low-Cost NO2 Sensor Using Machine Learning
PublikacjaAir 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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International Journal of Continuing Engineering Education and Lifelong Learning
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International Journal of Computer-Assisted Language Learning and Teaching
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International Journal of Web-Based Learning and Teaching Technologies
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International Journal for Research on Service-Learning and Community Engagement
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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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Electrical and noise responses of carbon nanotube networks enhanced by UV light for nitrogen dioxide sensing
Dane BadawczeNetworks consisting of randomly oriented carbon nanotubes (CNN) were investigated toward nitrogen dioxide detection by means of electrical and low-frequency noise measurements. UV-activation of CNN layers improved gas sensitivity and reduced the limit of detection, especially by employing 275 nm-LED. This data set includes DC resistance measurements...
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Video Classification Technology in a Knowledge-Vision-Integration Platform for Personal Protective Equipment Detection: An Evaluation
PublikacjaThis work is part of an effort for the development of a Knowledge-Vision Integration Platform for Hazard Control (KVIP-HC) in industrial workplaces, adaptable to a wide range of industrial environments. This paper focuses on hazards resulted from the non-use of personal protective equipment (PPE), and examines a few supervised learning techniques to compose the proposed system for the purpose of recognition of three protective...
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E-Learning as a Factor Optimizing the Amount of Work Time Devoted to Preparing an Exam for Medical Program Students during the COVID-19 Epidemic Situation
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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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Artificial Neural Networks as an architectural design tool- generating new detail forms based on the Roman Corinthian order capital
PublikacjaThe following paper presents the results of the research in the field of the machine learning, investigating the scope of application of the artificial neural networks algorithms as a tool in architectural design. The computational experiment was held using the backward propagation of errors method of training the artificial neural network, which was trained based on the geometry of the details of the Roman Corinthian order capital....
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Language Learning Journal (Formerly: British Journal of Language Teaching)
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Learning and Teaching-The International Journal of Higher Education in the Social Sciences
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International Journal of Practice-Based Learning in Health and Social Care
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Bożena Kostek prof. dr hab. inż.
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Using Moodle as a Solution to Interdisciplinary E-collaboration Issues
PublikacjaRapid technological development in recent years has contributed to numerous changes in many areas of life, including education and communication. Establishing interdisciplinary collaboration brings many benefits, however, it is often associated with numerous problems and inconveniences, as well as the need of constant improvement, lifelong learning, professional development (CPD) and finding an effective way of information transferring....
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Source code - AI models (MLM1-5 - series I-III - QNM opt)
Dane BadawczeSource 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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Predicting the Purchase of Electricity Prices for Renewable Energy Sources Based on Polish Power Grids Data Using Deep Learning Models for Controlling Small Hybrid PV Microinstallations
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Interactive Learning Environments
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Webquest- dobra praktyka w e-Learningu
PublikacjaW dobie informatyzacji i pokonywania barier wdrażania e-technologii na uczelniach wyższych uważa się, że jedną z najczęściej stosowanych aktywizujących technik nauczania wśród nauczycieli akademickich jest metoda projektu (ang. project-based learning). W niniejszym opracowaniu proponuje się zastosowanie w procesie edukacji na wyższej uczelni, metody webquest. Jest ona dużo rzadziej stosowana w praktyce. Opracowano ją w oparciu...
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CO-CURRICULAR ACTIVITIES IN TEACHING GEODESY
PublikacjaApart from education process based on the curricular activities, the whole set of co-curricular activities (CCAs) can help students to develope both expert knowledge and social skills. These activities are separated from academic course, sometimes placed outside of school or after regular school hours. Co-curricular activities such as students' scientific circles, workshops, conferences or festivals of science, publication, honor...
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Age Prediction from Low Resolution, Dual-Energy X-ray Images Using Convolutional Neural Networks
PublikacjaAge prediction from X-rays is an interesting research topic important for clinical applications such as biological maturity assessment. It is also useful in many other practical applications, including sports or forensic investigations for age verification purposes. Research on these issues is usually carried out using high-resolution X-ray scans of parts of the body, such as images of the hands or images of the chest. In this...
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Workshop on Logic and Learning
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Algorithmic Learning Theory
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Conference on Learning Theory (Annual Conference on Computational Learning Theory)
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Izabela Mironowicz dr hab. inż. arch.
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Jakub Szczepański prof. dr hab. inż. arch.
OsobyJakub Szczepański jest profesorem nadzwyczajnym na Wydziale Architektury Politechniki Gdańskiej, a od 2016 r. prodziekanem ds. nauki. Architekt, historyk architektury i konserwator zabytków. Jego badania koncentrują się na historii i architekturze Gdańska i miast Regionu Bałtyckiego, a także konserwacji dziedzictwa architektury osadzonych w problematyce współczesnych miast. Równolegle z pracą naukową na Politechnice Gdańskiej...
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Internet Journal on E-learning (Formerly : International Journal of Educational Telecommunications)
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TRWAŁOŚĆ PROJEKTU ERASMUS+ SP4CE - STUDIUM PRZYPADKU
PublikacjaProjekt ERASMUS+ Partnerstwo Strategiczne na Rzecz Kreatywności i Przedsiębiorczości (ang. Strategic Partnership for Creativity and Entrepreneurship - SP4CE) dotyczył wdrażania i upowszechniania innowacyjnych rozwiązań wzmacniających współpracę europejską w dziedzinie kształcenia i szkolenia zawodowego. Działania projektowe były związane z promowaniem innowacyjnych praktyk w edukacji oraz szkoleniach poprzez wspieranie spersonalizowanych...
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Classification of Covid-19 using Differential Evolution Chaotic Whale Optimization based Convolutional Neural Network
PublikacjaCOVID-19, also known as the Coronavirus disease-2019, is an transferrable disease that spreads rapidly, affecting countless individuals and leading to fatalities in this worldwide pandemic. The precise and swift detection of COVID-19 plays a crucial role in managing the pandemic's dissemination. Additionally, it is necessary to recognize COVID-19 quickly and accurately by investigating chest x-ray images. This paper proposed a...
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Weighted Clustering for Bees Detection on Video Images
PublikacjaThis work describes a bee detection system to monitor bee colony conditions. The detection process on video images has been divided into 3 stages: determining the regions of interest (ROI) for a given frame, scanning the frame in ROI areas using the DNN-CNN classifier, in order to obtain a confidence of bee occurrence in each window in any position and any scale, and form one detection window from a cloud of windows provided by...
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Cascade Object Detection and Remote Sensing Object Detection Method Based on Trainable Activation Function
PublikacjaObject detection is an important process in surveillance system to locate objects and it is considered as major application in computer vision. The Convolution Neural Network (CNN) based models have been developed by many researchers for object detection to achieve higher performance. However, existing models have some limitations such as overfitting problem and lower efficiency in small object detection. Object detection in remote...
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Greencoin: prototype of a mobile application facilitating and evidencing pro-environmental behavior of citizens
PublikacjaAmong many global challenges, climate change is one of the biggest challenges of our times. While it is one of the most devastating problems humanity has ever faced, one question naturally arises: can individuals make a difference? We believe that everyone can contribute and make a difference to the community and lives of others. However, there is still a lack of effective strategies to promote and facilitate pro-environmental...
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Conference on Computational Natural Language Learning (Conference on Natural Language Learning)
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Pedestrian detection in low-resolution thermal images
PublikacjaOver one million people die in car accidents worldwide each year. A solution that will be able to reduce situations in which pedestrian safety is at risk has been sought for a long time. One of the techniques for detecting pedestrians on the road is the use of artificial intelligence in connection with thermal imaging. The purpose of this work was to design a system to assist the safety of people and car intelligence with the use...
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Double Bias of Mistakes: Essence, Consequences, and Measurement Method
PublikacjaThere is no learning without mistakes. However, there is a clash between‘positive attitudes and beliefs’regarding learning processes and the ‘negative attitudes and beliefs’towardthese being accompanied bymistakes. Thisclash exposesa cognitive bias towardmistakesthat might block personal and organizational learning. This study presents an advanced measurement method to assess thebias of mistakes. The essence of it is the...
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Automatic classification and mapping of the seabed using airborne LiDAR bathymetry
PublikacjaShallow coastal areas are among the most inhabited areas and are valuable for biodiversity, recreation and the economy. Due to climate change and sea level rise, sustainable management of coastal areas involves extensive exploration, monitoring, and protection. Current high-resolution remote sensing methods for monitoring these areas include bathymetric LiDAR. Therefore, this study presents a novel methodological approach to assess...
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Detection of Anomalies in the Operation of a Road Lighting System Based on Data from Smart Electricity Meters
PublikacjaSmart meters in road lighting systems create new opportunities for automatic diagnostics of undesirable phenomena such as lamp failures, schedule deviations, or energy theft from the power grid. Such a solution fits into the smart cities concept, where an adaptive lighting system creates new challenges with respect to the monitoring function. This article presents research results indicating the practical feasibility of real‐time...