Wyniki wyszukiwania dla: Artificial intelligence - MOST Wiedzy

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Wyniki wyszukiwania dla: Artificial intelligence

Wyniki wyszukiwania dla: Artificial intelligence

  • AFarCloud Zagregowane rolnictwo w chmurze

    Projekty

    Kierownik projektu: dr hab. inż. Łukasz Kulas   Program finansujący: HORYZONT 2020

    Projekt realizowany w Katedra Inżynierii Mikrofalowej i Antenowej zgodnie z porozumieniem 783221 — AFarCloud z dnia 2018-05-17

  • Jacek Rumiński prof. dr hab. inż.

    Wykształcenie i kariera zawodowa 2022 2016   2002   1995   1991-1995 Tytuł profesora Habilitacja   Doktor nauk technicznych   Magister inżynier     Prezydent RP, dziedzina nauk inżynieryjno-technicznych, dyscyplina: inzyniera biomedyczna Politechnika Gdańska, Biocybernetyka i inżyniera biomedyczna, tematyka: „Metody wyodrębniania sygnałów i parametrów z różnomodalnych sekwencji obrazów dla potrzeb diagnostyki i wspomagania...

  • Milena Sobotka mgr inż.

  • Marek Galewski dr hab. inż.

    Mgr inż. - 2002r.  - Politechnika Gdańska; Wydział Elektroniki, Telekomunikacji i Informatyki; Automatyka i RobotykaDr inż. - 2007r. - Politechnika Gdańska; Wydział Mechaniczny; Budowa i eksploatacja maszynDr hab. inż. - 2016r. - Politechnika Gdańska; Wydział Mechaniczny; Budowa i eksploatacja maszyn Dotychczasowe i planowane obszary badań: Redukcja drgań podczas obróbki frezowaniem i toczeniem Zastosowanie zmiennej prędkości...

  • Cognitum Ontorion: Knowledge Representation and Reasoning System

    Publikacja

    At any point of human activity, knowledge and expertise are a key factors in understanding and solving any given problem. In present days, computer systems have the ability to support their users in an efficient and reliable way in gathering and processing knowledge. In this chapter we show how to use Cognitum Ontorion system in this areas. In first section, we identify emerging issues focused on how to represent and inference...

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  • SPECTRAL-BASED MODAL PARAMETERS IDENTIFICATION WITH MULTIPLE PARTICLE SWARMS OPTIMIZATION

    Publikacja

    The paper presents usage of a Particle Swarm Optimization [1] based algorithm for spectral-based modal parameters identification. The main algorithm consists of two groups of swarms, namely, scouts and helpers. For the first group additional penalizing process is provided to force separation of scouting swarms in frequency space. The swarms have an ability to communicate with each other. At first stage, each swarm focuses on a...

  • Automatic Breath Analysis System Using Convolutional Neural Networks

    Publikacja

    Diseases related to the human respiratory system have always been a burden for the entire society. The situation has become particularly difficult now after the outbreak of the COVID-19 pandemic. Even now, however, it is common for people to consult their doctor too late, after the disease has developed. To protect patients from severe disease, it is recommended that any symptoms disturbing the respiratory system be detected as...

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  • Qualia: About Personal Emotions Representing Temporal Form of Impressions - Implementation Hypothesis and Application Example

    Publikacja

    The aim of this article is to present the new extension of the xEmotion system as a computerized emotional system, part of an Intelligent System of Decision making (ISD) that combines the theories of affective psychology and philosophy of mind. At the same time, the authors try to find a practical impulse or evidence for a general reflection on the treatment of emotions as transitional states, which at some point may lead to the...

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  • Greencoin as an AI-Based Solution Shaping Climate Awareness.

    Publikacja

    Our research aim was to define possible AI-based solutions to be embedded in the Green- coin project, designed as a supportive tool for smart cities to achieve climate neutrality. We used Kamrowska-Załuska’s approach for evaluating AI-based solutions’ potential in urban planning. We narrowed down the research to the educational and economic aspects of smart cities. Furthermore, we used a systematic literature review. We propose...

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  • Recognition of Emotions in Speech Using Convolutional Neural Networks on Different Datasets

    Artificial Neural Network (ANN) models, specifically Convolutional Neural Networks (CNN), were applied to extract emotions based on spectrograms and mel-spectrograms. This study uses spectrograms and mel-spectrograms to investigate which feature extraction method better represents emotions and how big the differences in efficiency are in this context. The conducted studies demonstrated that mel-spectrograms are a better-suited...

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  • Nowe technologie w procesie projektowania architektonicznego

    Publikacja

    Projektowanie architektoniczne zmienia się wraz z wprowadzaniem nowych technologii. Zmiany, które są wynikiem cyfrowej rewolucji z końca XX wieku przyczyniły się do zmiany metod stosowanych w projektowaniu, ale nie sposobu myślenia o projektach i ich etapach. Można stwierdzić, że tradycyjna deska kreślarska została zastąpiona cyfrową. Jednak dziś w związku ze wzrostem skomplikowania procesów projektowych, ich wielowarstwowości...

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  • Impact of digital technologies on reliability of risk forecasting models - case study of enterprises in three global financial market regions

    Publikacja

    - Rok 2021

    This chapter focuses on the evaluation of impact of ICT on reliability of financial risk forecasting models. Presented study shows how the development of ICT can improve the effectiveness of such models. Determining a firm’s financial risk is one of the most interesting topics for investors and decision-makers. The multifaceted goal of the presented research is to separately estimate five traditional statistical and five soft computing...

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  • Multiple Cues-Based Robust Visual Object Tracking Method

    Publikacja
    • B. Khan
    • A. Jalil
    • A. Ali
    • K. Alkhaledi
    • K. Mehmood
    • K. M. Cheema
    • M. Murad
    • H. Tariq
    • A. M. El-Sherbeeny

    - Electronics - Rok 2022

    Visual object tracking is still considered a challenging task in computer vision research society. The object of interest undergoes significant appearance changes because of illumination variation, deformation, motion blur, background clutter, and occlusion. Kernelized correlation filter- (KCF) based tracking schemes have shown good performance in recent years. The accuracy and robustness of these trackers can be further enhanced...

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  • Data Acquisition and Processing for GeoAI Models to Support Sustainable Agricultural Practices

    Publikacja
    • A. G. Pereira
    • A. Ojo
    • C. Edward
    • L. Porwol

    - Rok 2020

    There are growing opportunities to leverage new technologies and data sources to address global problems related to sustainability, climate change, and biodiversity loss. The emerging discipline of GeoAI resulting from the convergence of AI and Geospatial science (Geo-AI) is enabling the possibility to harness the increasingly available open Earth Observation data collected from different constellations of satellites and sensors...

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  • Digital Interaction and Machine Intelligence. Proceedings of MIDI’2021 – 9th Machine Intelligence and Digital Interaction Conference, December 9-10, 2021, Warsaw, Poland

    Publikacja

    - Rok 2022

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  • Medical Image Dataset Annotation Service (MIDAS)

    Publikacja

    - Rok 2020

    MIDAS (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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  • Machine Learning and Deep Learning Methods for Fast and Accurate Assessment of Transthoracic Echocardiogram Image Quality

    Publikacja
    • W. Nazar
    • K. Nazar
    • L. Daniłowicz-Szymanowicz

    - Life - Rok 2024

    High-quality echocardiogram images are the cornerstone of accurate and reliable measurements of the heart. Therefore, this study aimed to develop, validate and compare machine learning and deep learning algorithms for accurate and automated assessment of transthoracic echocardiogram image quality. In total, 4090 single-frame two-dimensional transthoracic echocardiogram...

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  • Modified nanodiamond particle size studies by means of dynamic light scattering technique

    Publikacja

    - Rok 2022

    The Methods Utilizing the Phenomena of Light Scattering to Measure Particle Size distribution in different solvent, such as deionise water and alcohol and also to study the various structural formation when nanodiamond solution is placed on silicon surface. The purpose of this research project is divided into two parts to configure the measurement units for examining modified nanodiamond particles, examination...

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  • Modified nanodiamond particle size studies by means of dynamic light scattering technique

    Publikacja

    - Rok 2022

    The Methods Utilizing the Phenomena of Light Scattering to Measure Particle Size distribution in different solvent, such as deionise water and alcohol and also to study the various structural formation when nanodiamond solution is placed on silicon surface. The purpose of this research project is divided into two parts to configure the measurement units for examining modified nanodiamond particles, examination...

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  • Possible uses of crisis situation aiding system in virtual world simulation

    Many of the real world crisis situations like spreading fire, hostile units attack, flood, and etc. are commonly used in computer games where a simulation of extensive virtual world is crucial. This paper presents some ideas for possible uses of existing crisis situation aiding system in such environments. Moreover, it shows how this kind of system can be taught during subsequent games with a large number of players. As an example...

  • Smart experience engineering to support collaborative design problems based on constraints modelling

    Publikacja

    Engineering design is a knowledge intensive process. Experts' experiences from different product life-cycle stages play a key role in problem solving during design decision making by linking up knowledge to find better solutions for a specific design problem. Different approaches have been used to support Collaborative and Concurrent Product Design, such as Constraint Satisfaction Problem (CSP) modelling. Additionally, due to the...

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  • INDIRECT CONTROL OVER SUBORDINATE UNITS

    Developing a game universe usually involves creation of various units which can be both, encountered by a player or controlled by him. There is a number of works considering autonomous behaviors of units wandering around the game world. When it comes to the units controlled by the player, they are often deprived of autonomy and are strictly controlled by the player. This paper presents a concept of units behavior depending on their...

  • Visual Features for Endoscopic Bleeding Detection

    Aims: To define a set of high-level visual features of endoscopic bleeding and evaluate their capabilities for potential use in automatic bleeding detection. Study Design: Experimental study. Place and Duration of Study: Department of Computer Architecture, Faculty of Electronics, Telecommunications and Informatics, Gdansk University of Technology, between March 2014 and May 2014. Methodology: The features have...

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  • Antropoidalny Model Inteligentnego Systemu Decyzyjnego dla Jednostek Autonomicznych

    Publikacja

    - Rok 2017

    Głównym celem pracy jest opracowanie modelu procesów psychologicznych -- od momentu otrzymania bodźca do momentu podjęcia adekwatnej reakcji -- zachodzących w mózgu człowieka (psychologia poznawcza), oraz teorii motywacji (potrzeb, popędów i emocji). Model, zaprezentowany w pracy nazwany Inteligentnym Systemem Decyzyjnym (ISD), może mieć zastosowanie w systemie sterowania jednostką autonomiczną (agentem). W rozprawie rozważa się...

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  • Integration of brood units in game universe

    Publikacja

    - Rok 2011

    An access to a great number of various services allows for decomposition of complex problems Developing a game universe usually involves creation of various units which can be encountered by a player. Those can be lonely or organized in broods animals and monsters wandering around the game world. In order to provide natural gaming experience those units should behave variously depending on the world situation. Those behaviours...

  • The impact of the temperament model on the behavior of an autonomous driver

    Because it is generally believed that the personality and temperament of a human driver influence his/her behavior on the road, the article presents a computational model of the temperament of an autonomous agent - a driver. First, a short review of the four ideas of Galen’s temperament in psychology is presented. Temperament traits are grouped into four other sets, one of which is chosen for implementation in the project of integration...

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  • JamesBot - an intelligent agent playing StarCraft II

    Publikacja

    The 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 LEARNING OF STRATEGY AND RULES IN CARD GAMES USING IMAGE FROM CAMERA

    Publikacja

    Below 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...

  • Adjusting Game Difficulty by Recreating Behavioral Trees of Human Player Actions

    Publikacja

    - Rok 2013

    This paper presents a proposition of a method for adjusting game difficulty to the current level of player's skills in one-on-one games. The method is based on recognition of human player's actions and recording of those actions in the form of behavioral trees. Such trees are later used to drive behaviors of computer-controlled opponents so that human player has beat hit own strategy and improve on it, to win subsequent games....

  • Social media and efficient computer infrastructure in smart city

    Publikacja

    - Rok 2018

    Social media require an efficient infrastructures of computer and communication systems to support a smart city. In a big city, there are several crucial dilemmas with a home and public space planning, a growing population, a global warming, carbon emissions, a lack of key resources like water and energy, and a traffic congestion. In a smart city, we expect an efficient and sustainable transportation, efficient management of resources...

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  • Neural network based algorithm for hand gesture detection in a low-cost microprocessor applications

    In this paper the simple architecture of neural network for hand gesture classification was presented. The network classifies the previously calculated parameters of EMG signals. The main goal of this project was to develop simple solution that is not computationally complex and can be implemented on microprocessors in low-cost 3D printed prosthetic arms. As the part of conducted research the data set EMG signals corresponding...

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  • Potential and Use of the Googlenet Ann for the Purposes of Inland Water Ships Classification

    Publikacja

    - Polish Maritime Research - Rok 2020

    This article presents an analysis of the possibilities of using the pre-degraded GoogLeNet artificial neural network to classify inland vessels. Inland water authorities monitor the intensity of the vessels via CCTV. Such classification seems to be an improvement in their statutory tasks. The automatic classification of the inland vessels from video recording is a one of the main objectives of the Automatic Ship Recognition and...

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  • LDNet: A Robust Hybrid Approach for Lie Detection Using Deep Learning Techniques

    Publikacja
    • S. A. Prome
    • M. R. Islam
    • D. Asirvatham
    • N. A. Ragavan
    • C. Sanín
    • E. Szczerbicki

    - CMC-Computers Materials & Continua - Rok 2024

    Deception detection is regarded as a concern for everyone in their daily lives and affects social interactions. The human face is a rich source of data that offers trustworthy markers of deception. The deception or lie detection systems are non-intrusive, cost-effective, and mobile by identifying facial expressions. Over the last decade, numerous studies have been conducted on deception detection using several advanced techniques....

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  • Optimizing Control of Wastewater Treatment Plant With Reinforcement Learning: Technical Evaluation of Twin-Delayed Deep Deterministic Policy Gradient Agent

    Publikacja

    Control of the wastewater treatment processes presents significant challenges due to the fluctuating nature of inflow and wastewater composition, alongside the system’s non-linear dynamics. Traditional control methods struggle to adapt to these variations, leading to an economically suboptimal operation of the process and a violation of norms imposed on the quality of wastewater discharged to the catchment area. This study proposes...

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  • Skills mismatch in the context of technological change

    Publikacja

    - Rok 2022

    The main purpose of this dissertation is to assess the perception asymmetry of smart skills and formal education in ICT based economy. In other words, the goal of this research is to assess perceptions of smart skills and competences in the context of technological change from the perspectives of employers and students in Poland. Determining the fore-mentioned relationship gives insight into the hypothetical perception asymmetry...

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  • Application of fiber optic sensors using Machine Learning algorithms for temperature measurement of lithium-ion batteries

    Optical fiber sensorsusing low-coherence interferometry require processing ofthe output spectrum or interferogramto quickly and accurately determine the instantaneous value of the measured quantity, such as temperature.Methods based on machine learning are a good candidate for this application. The application of four such methods in an optical fiber temperature sensoris demonstrated.Using aZnO-coated...

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  • Visual Features for Improving Endoscopic Bleeding Detection Using Convolutional Neural Networks

    Publikacja

    The presented paper investigates the problem of endoscopic bleeding detection in endoscopic videos in the form of a binary image classification task. A set of definitions of high-level visual features of endoscopic bleeding is introduced, which incorporates domain knowledge from the field. The high-level features are coupled with respective feature descriptors, enabling automatic capture of the features using image processing methods....

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  • Adam Brzeski dr inż.

  • Maciej Bobowicz Ph.D., M.D.

    Osoby

  • Michał Lech dr inż.

    Osoby

    Michał Lech was born in Gdynia in 1983. In 2007 he graduated from the faculty of Electronics, Telecommunications and Informatics of Gdansk University of Technology. In June 2013, he received his Ph.D. degree. The subject of the dissertation was: “A Method and Algorithms for Controlling the Sound Mixing Processes with Hand Gestures Recognized Using Computer Vision”. The main focus of the thesis was the bias of audio perception caused...

  • Paweł Syty dr inż.

  • Tomasz Białaszewski dr inż.

  • Paweł Rościszewski dr inż.

    Osoby

    Paweł Rościszewski received his PhD in Computer Science at Gdańsk University of Technology in 2018 based on PhD thesis entitled: "Optimization of hybrid parallel application execution in heterogeneous high performance computing systems considering execution time and power consumption". Currently, he is an Assistant Professor at the Faculty of Electronics, Telecommunications and Informatics, Gdańsk University of Technology, Poland....

  • Dawid Wieczerzak mgr inż.

    Osoby

  • Kacper Cierpiak

    Osoby

  • Barbara Klaudel

    Osoby

  • Hossein Nejatbakhsh Esfahani Dr.

    Osoby

    My research interests lie primarily in the area of Learning-based Safety-Critical Control Systems, for which I leverage the following concepts and tools:-Robust/Optimal Control-Reinforcement Learning-Model Predictive Control-Data-Driven Control-Control Barrier Function-Risk-Averse Controland with applications to:-Aerial and Marine robotics (fixed-wing UAVs, autonomous ships and underwater vehicles)-Multi-Robot and Networked Control...

  • Leszek Chomacki Dr inż.

    Osoby

  • Muhammad Jamshed Abbass Phd in Electrical Engineering

    Osoby

    Muhammad Jamshed Abbass received the M.S. degree in electrical engineering from Riphah International University, Islamabad. He is currently pursuing the Ph.D. degree with the Wrocław University of Science and Technology, Wroclaw, Poland. His research interests include machine learning, voltage stability within power systems, control design, analysis, the modeling of electrical power systems, the integration of numerous decentralized...

  • Radosław Roszczyk dr inż.

    Osoby