Wyniki wyszukiwania dla: MACHINE LEARNING, DEEP NEURAL NETWORKS, CEREBRAL MICROBLEEDS, CMB DETECTION, MR IMAGES

• Olgun Aydin dr

  Osoby

  Katedra Statystyki i Ekonometrii

  Olgun Aydin finished his PhD by publishing a thesis about Deep Neural Networks. He works as a Principal Machine Learning Engineer in Nike, and works as Assistant Professor in Gdansk University of Technology in Poland. Dr. Aydin is part of editorial board of "Journal of Artificial Intelligence and Data Science" Dr. Aydin served as Vice-Chairman of Why R? Foundation and is member of Polish Artificial Intelligence Society. Olgun is...

• A Comprehensive Analysis of Deep Neural-Based Cerebral Microbleeds Detection System

  Publikacja

  • M. Ferlin
  • M. Grochowski
  • A. Kwasigroch
  • A. Mikołajczyk-Bareła
  • E. Szurowska
  • M. Grzywińska
  • A. Sabisz

  - Electronics - Rok 2021

  Machine learning-based systems are gaining interest in the field of medicine, mostly in medical imaging and diagnosis. In this paper, we address the problem of automatic cerebral microbleeds (CMB) detection in magnetic resonance images. It is challenging due to difficulty in distinguishing a true CMB from its mimics, however, if successfully solved it would streamline the radiologists work. To deal with this complex three-dimensional...

  Pełny tekst do pobrania w portalu

• Deep neural networks for data analysis 24/25

  Kursy Online

  • J. Cychnerski
  • K. Draszawka

  This course covers introduction to supervised machine learning, construction of basic artificial deep neural networks (DNNs) and basic training algorithms, as well as the overview of popular DNNs architectures (convolutional networks, recurrent networks, transformers). The course introduces students to popular regularization techniques for deep models. Besides theory, large part of the course is the project in which students apply...

• Deep Learning Basics 2023/24

  Kursy Online

  • K. Draszawka

  A course about the basics of deep learning intended for students of Computer Science. It includes an introduction to supervised machine learning, the architecture of basic artificial neural networks and their training algorithms, as well as more advanced architectures (convolutional networks, recurrent networks, transformers) and regularization and optimization techniques.

• Olgun Aydin Dr

  Osoby

  Olgun Aydin finished his PhD by publishing a thesis about Deep Neural Networks. He works as a Senior Data Scientist in PwC Poland, gives lectures in Gdansk University of Technology in Poland and member of WhyR? Foundation. Olgun is a very big fan of R and author of the book called “R Web Scraping Quick Start Guide” , two video courses are called “Deep Dive into Statistical Modelling using R” and “Applied Machine Learning and Deep...

• SegSperm - a dataset of sperm images for blurry and small object segmentation

  Dane Badawcze

  open access

  • E. Lewandowska
  • D. Węsierski
  • M. Mazur-Milecka
  • J. Liss
  • A. Jezierska

  Many deep learning applications require figure-ground segmentation. The performance of segmentation models varies across modalities and acquisition settings.

• Neural networks and deep learning

  Publikacja

  • A. P. López-Monroy
  • J. S. Garcia Salinas

  - Rok 2022

  In this chapter we will provide the general and fundamental background related to Neural Networks and Deep Learning techniques. Specifically, we divide the fundamentals of deep learning in three parts, the first one introduces Deep Feed Forward Networks and the main training algorithms in the context of optimization. The second part covers Convolutional Neural Networks (CNN) and discusses their main advantages and shortcomings...

  Pełny tekst do pobrania w serwisie zewnętrznym

• Face with Mask Detection in Thermal Images Using Deep Neural Networks

  Publikacja

  • N. Kowalczyk
  • J. Rumiński

  - SENSORS - Rok 2021

  As the interest in facial detection grows, especially during a pandemic, solutions are sought that will be effective and bring more benefits. This is the case with the use of thermal imaging, which is resistant to environmental factors and makes it possible, for example, to determine the temperature based on the detected face, which brings new perspectives and opportunities to use such an approach for health control purposes. The...

  Pełny tekst do pobrania w portalu

• Adaptacyjny system oświetlania dróg oraz inteligentnych miast

  Publikacja

  • T. Śmiałkowski

  - Rok 2024

  Przedmiotem rozprawy jest zbadanie praktycznej możliwości wykrywania w czasie rzeczywistym anomalii w systemie oświetlenia drogowego w oparciu o analizę danych ze inteligentnych liczników energii. Zastosowanie inteligentnych liczników energii elektrycznej (Smart Meter) w systemach oświetlenia drogowego stwarza nowe możliwości w zakresie automatycznej diagnostyki takich niepożądanych zjawisk jak awarie lamp, odstępstwa od harmonogramu...

  Pełny tekst do pobrania w portalu

• Deep neural networks for data analysis

  Kursy Online

  • K. Draszawka

  The aim of the course is to familiarize students with the methods of deep learning for advanced data analysis. Typical areas of application of these types of methods include: image classification, speech recognition and natural language understanding. Celem przedmiotu jest zapoznanie studentów z metodami głębokiego uczenia maszynowego na potrzeby zaawansowanej analizy danych. Do typowych obszarów zastosowań tego typu metod należą:...