Wyszukiwarka
Filtry
wszystkich: 1176
-
Katalog
- Publikacje 816 wyników po odfiltrowaniu
- Czasopisma 10 wyników po odfiltrowaniu
- Konferencje 5 wyników po odfiltrowaniu
- Osoby 40 wyników po odfiltrowaniu
- Projekty 2 wyników po odfiltrowaniu
- Laboratoria 1 wyników po odfiltrowaniu
- Kursy Online 19 wyników po odfiltrowaniu
- Wydarzenia 4 wyników po odfiltrowaniu
- Dane Badawcze 279 wyników po odfiltrowaniu
wyświetlamy 1000 najlepszych wyników Pomoc
Wyniki wyszukiwania dla: BIG DATA DEEP LEARNING REMOTE MEDICAL DIAGNOSTIC
-
Tomasz Dziubich dr inż.
OsobyWykonane projekty badawcze i celowe Internetowa platforma integracji danych i współpracy medycznych zespołów badawczych dla potrzeb ośrodków udarowych 2013 - 2016 MAYDAY EURO 2012 Superkomputerowa platforma kontekstowej analizy strumieni danych multimedialnych do identyfikacji wyspecyfikowanych obiektów lub niebezpiecznych zdarzeń – zadanie (Rozwój algorytmów i budowa aplikacji wspomagających badania medyczne), 2008-2012 Rozwój...
-
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.
-
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...
-
Remote measurement of building usable floor area - Algorithms fusion
PublikacjaRapid changes that are taking place in the urban environment have significant impact on urban growth. Most cities and urban regions all over the world compete to increase resident and visitor satisfaction. The growing requirements and rapidity of introducing new technologies to all aspects of residents' lives force cities and urban regions to implement "smart cities" concepts in their activities. Real estate is one of the principal...
-
Reliability of Pulse Measurements in Videoplethysmography
PublikacjaReliable, remote pulse rate measurement is potentially very important for medical diagnostics and screening. In this paper the Videoplethysmography was analyzed especially to verify the possible use of signals obtained for the YUV color model in order to estimate the pulse rate, to examine what is the best pulse estimation method for short video sequences and finally, to analyze how potential PPG-signals can be distinguished from...
-
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...
-
An Intelligent Approach to Short-Term Wind Power Prediction Using Deep Neural Networks
PublikacjaIn this paper, an intelligent approach to the Short-Term Wind Power Prediction (STWPP) problem is considered, with the use of various types of Deep Neural Networks (DNNs). The impact of the prediction time horizon length on accuracy, and the influence of temperature on prediction effectiveness have been analyzed. Three types of DNNs have been implemented and tested, including: CNN (Convolutional Neural Networks), GRU (Gated Recurrent...
-
Spotkanie politechnicznego klubu sztucznej inteligencji
WydarzeniaPierwsze w tym roku akademickim spotkanie klubu AI Bay – Zatoka Sztucznej Inteligencji, który działa na Politechnice Gdańskiej odbędzie się w Gmachu B Wydziału Elektroniki, Telekomunikacji i Informatyki (Audytorium 1P).
-
Algorithmic Human Resources Management - Perspectives and Challenges
PublikacjaTheoretical background: Technology – most notably processes of digitalisation, the use of artificial intelligence, machine learning, big data and prevalence of remote work due to pandemic – changes the way organizations manage human resources. One of the increasing trends is the use of so-called “algorithmic management”. It is notably different than previous e-HRM or HRIS (human resources information systems) applications, as it...
-
Method of selective fading as a educational tool to study the behaviour of prestressed concrete elements under excess loading
PublikacjaPrestressed structures are a key to realization of the boldest architectural ideas, characteristic feature of prestressed structure is better use of concrete material properties by insertion of internal forces. Learning about pre-stressed reinforced concrete structures is an integral part of Graduate Studies Program in construction engineering. Know-how of geometry change patterns in prestressed concrete elements under certain...
-
Multiplicative Long Short-Term Memory with Improved Mayfly Optimization for LULC Classification
PublikacjaLand Use and Land Cover (LULC) monitoring is crucial for global transformation, sustainable land control, urban planning, urban growth prediction, and the establishment of climate regulations for long-term development. Remote sensing images have become increasingly important in many environmental planning and land use surveys in recent times. LULC is evaluated in this research using the Sat 4, Sat 6, and Eurosat datasets. Various...
-
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...
-
Jarosław Chojnacki prof. dr hab. inż.
OsobyUrodzony w 1961 w Bydgoszczy, absolwent Technikum Chemicznego im. I. Łukasiewicza w Bydgoszczy. Studia chemiczne ukończył na Wydziale Chemicznym Politechniki Gdańskiej w 1986 roku, broniąc pracy dotyczącej elektrod jonoselektywnych. Późniejsze badania związane były z syntezą organiczną i krzemoorganiczną a od 2002 roku z krystalografią. Praca doktorska dotyczyła silanotiolanów miedziowców, a dysertacja habilitacyjna (2010) opisywała...
-
Real-Time Facial Features Detection from Low Resolution Thermal Images with Deep Classification Models
PublikacjaDeep networks have already shown a spectacular success for object classification and detection for various applications from everyday use cases to advanced medical problems. The main advantage of the classification models over the detection models is less time and effort needed for dataset preparation, because classification networks do not require bounding box annotations, but labels at the image level only. Yet, after passing...
-
IEEE/ACM International Conference on Big Data Computing, Applications and Technologies
Konferencje -
Template chart detection for stoma telediagnosis
PublikacjaThe paper presents the concept of using color template charts for the needs of telemedicine, particularly telediagnosis of the stoma. Although the concept is not new, the current popularity and level of development of digital cameras, especially those embedded in smartphones, allow common and reliable remote advice on various medical problems, which can be very important in the case of limitations in a physical contact with a doctor....
-
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...
-
Application of Wavelet Transform and Fractal Analysis for Esophageal pH-Metry to Determine a New Method to Diagnose Gastroesophageal Reflux Disease
PublikacjaIn this paper, a new method for analysing gastroesophageal reflux disease (GERD) is shown. This novel method uses wavelet transform (WT) and wavelet-based fractal analysis (WBFA) on esophageal pH-metry measurements. The esophageal pH-metry is an important diagnostic tool supporting the physician’s work in diagnosing some forms of reflux diseases. Interpreting the results of 24-h pH-metry monitoring is time-consuming, and the conclusions...
-
Musical Instrument Tagging Using Data Augmentation and Effective Noisy Data Processing
PublikacjaDeveloping signal processing methods to extract information automatically has potential in several applications, for example searching for multimedia based on its audio content, making context-aware mobile applications (e.g., tuning apps), or pre-processing for an automatic mixing system. However, the last-mentioned application needs a significant amount of research to reliably recognize real musical instruments in recordings....
-
Reinforcement Learning Algorithm and FDTD-based Simulation Applied to Schroeder Diffuser Design Optimization
PublikacjaThe aim of this paper is to propose a novel approach to the algorithmic design of Schroeder acoustic diffusers employing a deep learning optimization algorithm and a fitness function based on a computer simulation of the propagation of acoustic waves. The deep learning method employed for the research is a deep policy gradient algorithm. It is used as a tool for carrying out a sequential optimization process the goal of which is...
-
Informal Workplace Learning and Employee Development. Growing in the Organizational New Normal
PublikacjaThe new paradigm in employee development assumes that employees should proactively direct their learning and growth. Most workplace learning is basically informal and occurs through daily work routines, peer-to-peer interactions, networking, and typically brings about significant positive outcomes to both individuals and organizations. Yet, workplace learning always occurs in a pre-defined context and this context has recently...
-
Podstawy uczenia głębokiego 2022
Kursy Online{mlang pl}Kurs podstaw uczenia głębokiego przeznaczony dla studentów kierunku Informatyka.{mlang} {mlang en}This is a course about deep learning basics dedicated for Computer Science students.{mlang}
-
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...
-
Human Feedback and Knowledge Discovery: Towards Cognitive Systems Optimization
PublikacjaCurrent computer vision systems, especially those using machine learning techniques are data-hungry and frequently only perform well when dealing with patterns they have seen before. As an alternative, cognitive systems have become a focus of attention for applications that involve complex visual scenes, and in which conditions may vary. In theory, cognitive applications uses current machine learning algorithms, such as deep learning,...
-
Benchmarking Deep Neural Network Training Using Multi- and Many-Core Processors
PublikacjaIn the paper we provide thorough benchmarking of deep neural network (DNN) training on modern multi- and many-core Intel processors in order to assess performance differences for various deep learning as well as parallel computing parameters. We present performance of DNN training for Alexnet, Googlenet, Googlenet_v2 as well as Resnet_50 for various engines used by the deep learning framework, for various batch sizes. Furthermore,...
-
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...
-
Evaluation of Respiration Rate Using Thermal Imaging in Mobile Conditions
PublikacjaRespiratory rate is very important vital sign that should be measured and documented in many medical situations. The remote measurement of respiration rate can be especially valuable for medical screening purposes (e.g. severe acute respiratory syndrome (SARS), pandemic influenza, etc.). In this chapter we present a review of many different studies focused on the measurements and estimation of respiration rate using thermal imaging...
-
Changes in psychological distress among Polish medical university teachers during the COVID-19 pandemic
PublikacjaOur study aims to update knowledge about psychological distress and its changes in the Polish group of academic medical teachers after two years of a global pandemic. During the coronavirus disease, teachers were challenged to rapidly transition into remote teaching and adapt new assessment and evaluation systems for students, which might have been...
-
Underground Water Level Prediction in Remote Sensing Images Using Improved Hydro Index Value with Ensemble Classifier
PublikacjaThe economic sustainability of aquifers across the world relies on accurate and rapid estimates of groundwater storage changes, but this becomes difficult due to the absence of insitu groundwater surveys in most areas. By closing the water balance, hydrologic remote sensing measures offer a possible method for quantifying changes in groundwater storage. However, it is uncertain to what extent remote sensing data can provide an...
-
Improving Accuracy of Respiratory Rate Estimation by Restoring High Resolution Features With Transformers and Recursive Convolutional Models
PublikacjaNon-contact evaluation of vital signs has been becoming increasingly important, especially in light of the COVID- 19 pandemic, which is causing the whole world to examine people’s interactions in public places at a scale never seen before. However, evaluating one’s vital signs can be a relatively complex procedure, which requires both time and physical contact between examiner and examinee. These re- quirements limit the number...
-
International Conference on Intelligent Data Engineering and Automated Learning
Konferencje -
Method for Clustering of Brain Activity Data Derived from EEG Signals
PublikacjaA method for assessing separability of EEG signals associated with three classes of brain activity is proposed. The EEG signals are acquired from 23 subjects, gathered from a headset consisting of 14 electrodes. Data are processed by applying Discrete Wavelet Transform (DWT) for the signal analysis and an autoencoder neural network for the brain activity separation. Processing involves 74 wavelets from 3 DWT families: Coiflets,...
-
Dorota Dominika Kamrowska-Załuska dr hab. inż. arch.
OsobyDr hab. inż. arch. Dorota Kamrowska-Załuska, profesorka Politechniki Gdańskiej, jest od 2002 roku związana z Katedrą Urbanistyki i Planowania Regionalnego na Wydziale Architektury Politechniki Gdańskiej. Wieloletnia Kierowniczka Studiów Podyplomowych Urbanistyki i Gospodarki Przestrzennej „Projektowanie przestrzeni i zarządzanie”, odbyła staże badawcze w kilku instytucjach badawczych w tym Massachusetts Institute of Technology...
-
Design of a Distributed System using Mobile Devices and Workflow Management for Measurement and Control of a Smart Home and Health
PublikacjaThe paper presents design of a distributed system for measurements and control of a smart home including temper- atures, light, fire danger, health problems of inhabitants such as increased body temperature, a person falling etc. This is done by integration of mobile devices and standards, distributed service based middleware BeesyCluster and a workflow management system. Mobile devices are used to measure the parameters and are...
-
A novel architecture of Web-GIS for mapping and analysis of echinococcosis in Poland
PublikacjaEchinococcosis is an infectious disease transferred through ingestion of food or water which have been contaminated with eggs of the Echinococcus tapeworm, which are spread by intermediate parasite hosts. Because the latter are primarily territorial, research related to diagnosis and prevention of echinococcosis requires investigation of environmental factors, which can be supported with the use of a Geographical Information System...
-
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...
-
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...
-
Assessing the attractiveness of human face based on machine learning
PublikacjaThe attractiveness of the face plays an important role in everyday life, especially in the modern world where social media and the Internet surround us. In this study, an attempt to assess the attractiveness of a face by machine learning is shown. Attractiveness is determined by three deep models whose sum of predictions is the final score. Two annotated datasets available in the literature are employed for training and testing...
-
Deep CNN based decision support system for detection and assessing the stage of diabetic retinopathy
PublikacjaThe diabetic retinopathy is a disease caused by long-standing diabetes. Lack of effective treatment can lead to vision impairment and even irreversible blindness. The disease can be diagnosed by examining digital color fundus photographs of retina. In this paper we propose deep learning approach to automated diabetic retinopathy screening. Deep convolutional neural networks (CNN) - the most popular kind of deep learning algorithms...
-
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...
-
Experience-Based Cognition for Driving Behavioral Fingerprint Extraction
PublikacjaABSTRACT With the rapid progress of information technologies, cars have been made increasingly intelligent. This allows cars to act as cognitive agents, i.e., to acquire knowledge and understanding of the driving habits and behavioral characteristics of drivers (i.e., driving behavioral fingerprint) through experience. Such knowledge can be then reused to facilitate the interaction between a car and its driver, and to develop better and...
-
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...
-
Mirosław Andrusiewicz prof. dr hab. n. med. i n. o zdr.
OsobyPosiadane dyplomy, stopnie naukowe lub artystyczne ̶ stopień doktora habilitowanego nauk medycznych (dyscyplina biologia medyczna) z dnia 4 grudnia 2017 r. Tytuł osiągnięcia naukowego: „Analiza wybranych genów związanych z przebiegiem zmian patologicznych w komórkach wywodzących się z żeńskich wewnętrznych narządów płciowych”; Uniwersytet Medyczny im. Karola Marcinkowskiego w Poznaniu, Wydział Lekarski II; recenzenci: Prof....
-
A comparative analysis of methods and tools for low impact development (LID) site selection
PublikacjaThe site selection for Low Impact Development (LID) practices is a significant process. It affects the effectiveness of LID in controlling stormwater surface runoff, volume, flow rate, and infiltration. This research paper presents a comprehensive review of various methods used for LID site selection. It starts by introducing different methods and tools. Three main methods: index-based methods, GIS-based multi-criteria decision...
-
DUABI - Business Intelligence Architecture for Dual Perspective Analytics
PublikacjaA significant expansion of Big Data and NoSQL databases made it necessary to develop new architectures for Business Intelligence systems based on data organized in a non-relational way. There are many novel solutions combining Big Data technologies with Data Warehousing. However, the proposed solutions are often not sufficient enough to meet the increasing business demands, such as low data latency while still maintaining high...
-
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...
-
How personality traits, sports anxiety, and general imagery could influence the physiological response measured by SCL to imagined situations in sports?
Dane BadawczeThe data were collected to understand how individual differences in personality (e.g. neuroticism), general imagery, and situational sports anxiety are linked to arousal measuring with skin conductance level (SCL) in situational imagery (as scripted for sport-related scenes). Thirty persons participated in the study, aged between 14 and 42 years, with...
-
WEB-CAM AS A MEANS OF INFORMATION ABOUT EMOTIONAL ATTEMPT OF STUDENTS IN THE PROCESS OF DISTANT LEARNING
PublikacjaNew methods in education become more popular nowadays. Distant learning is a good example when teacher and student meet in virtual environment. Because interaction in this virtual world might be complicated it seems necessary to assure as much methods of conforming that student is still engaged in the process of learning as it is possible. We would like to present assumption that by means of web-cam we will be able to track facial...
-
Technologia medyczna w obiektach świadczących usługi lecznicze- Medical technology in healthcare facilities
PublikacjaArchitektura budynków szpitalnych kreowana jest pod silnym wpływem wymagań sanitarno-higienicznych oraz wytycznych wynikających z charakteru świadczonych usług medycznych. Naczelną rolę odgrywa tu technologia medyczna, która jest zasobem wiedzy, procesów organizacyjnych i środków fizycznych uczestniczących w realizacji zdefiniowanych świadczeń zdrowotnych. Istotnym elementem takiej kreacji architektonicznej jest szereg procesów...
-
Protokoły łączności do transmisji strumieni multimedialnych na platformie KASKADA
PublikacjaPlatforma KASKADA rozumiana jako system przetwarzania strumieni multimedialnych dostarcza szeregu usług wspomagających zapewnienie bezpieczeństwa publicznego oraz ocenę badań medycznych. Wydajność platformy KASKADA w znaczącym stopniu uzależniona jest od efektywności metod komunikacji, w tym wymiany danych multimedialnych, które stanowią podstawę przetwarzania. Celem prowadzonych prac było zaprojektowanie podsystemu komunikacji...