Wyniki wyszukiwania dla: WAVE-U-NET - MOST Wiedzy

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Wyniki wyszukiwania dla: WAVE-U-NET

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Wyniki wyszukiwania dla: WAVE-U-NET

  • Automatic audio signal mixing system based on one-dimensional Wave-U-Net autoencoders

    Publikacja

    - Rok 2023

    The purpose of this dissertation is to develop an automatic song mixing system that is capable of automatically mixing a song with good quality in any music genre. This work recalls first the audio signal processing methods used in audio mixing, and it describes selected methods for automatic audio mixing. Then, a novel architecture built based on one-dimensional Wave-U-Net autoencoders is proposed for automatic music mixing. Models...

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  • Automatic music signal mixing system based on one-dimensional Wave-U-Net autoencoders

    The purpose of this paper is to show a music mixing system that is capable of automatically mixing separate raw recordings with good quality regardless of the music genre. This work recalls selected methods for automatic audio mixing first. Then, a novel deep model based on one-dimensional Wave-U-Net autoencoders is proposed for automatic music mixing. The model is trained on a custom-prepared database. Mixes created using the...

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  • Urban scene semantic segmentation using the U-Net model

    Publikacja

    - Rok 2023

    Vision-based semantic segmentation of complex urban street scenes is a very important function during autonomous driving (AD), which will become an important technology in industrialized countries in the near future. Today, advanced driver assistance systems (ADAS) improve traffic safety thanks to the application of solutions that enable detecting objects, recognising road signs, segmenting the road, etc. The basis for these functionalities...

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  • Smart Approach for Glioma Segmentation in Magnetic Resonance Imaging using Modified Convolutional Network Architecture (U-NET)

    Publikacja

    - CYBERNETICS AND SYSTEMS - Rok 2021

    Segmentation 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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  • CONTROL OF THE WAVES IN A TOWING TANK WITH THE USE OF A BLACK-BOX MODEL

    The paper describes an adaptive control system of the waves, implemented in the Ship Design and Research Centre, CTO S.A. The purpose of generating the waves in the towing tank is the modelling of the environmental conditions during hydrodynamic model tests. The tests are performed on scale models of towed or free running ships, anchored structures like oil rigs or bottommounted structures, e.g. wind turbines. In the towing tank...

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  • Detection of the Oocyte Orientation for the ICSI Method Automation

    Automation or even computer assistance of the popular infertility treatment method: ICSI (Intracytoplasmic Sperm Injection) would speed up the whole process and improve the control of the results. This paper introduces a preliminary research for automatic spermatozoon injection into the oocyte cytoplasm. Here, the method for detection a correct orientation of the polar body of the oocyte is presented. Proposed method uses deep...

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  • Comparison of image pre-processing methods in liver segmentation task

    Automatic liver segmentation of Computed Tomography (CT) images is becoming increasingly important. Although there are many publications in this field there is little explanation why certain pre-processing methods were utilised. This paper presents a comparison of the commonly used approach of Hounsfield Units (HU) windowing, histogram equalisation, and a combination of these methods to try to ascertain what are the differences...

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  • Abdominal Aortic Aneurysm segmentation from contrast-enhanced computed tomography angiography using deep convolutional networks

    Publikacja
    • T. Dziubich
    • P. Białas
    • Ł. Znaniecki
    • J. Halman
    • J. Brzeziński

    - Rok 2020

    One of the most common imaging methods for diagnosing an abdominal aortic aneurysm, and an endoleak detection is computed tomography angiography. In this paper, we address the problem of aorta and thrombus semantic segmentation, what is a mandatory step to estimate aortic aneurysm diameter. Three end-to-end convolutional neural networks were trained and evaluated. Finally, we proposed an ensemble of deep neural networks with underlying...

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  • Measurement system based on USB Z-Wave controller

    A wireless measurement system based on the Z-Wave standard is presented in this paper. The system is composed of a U SB Z-Stick Gen5 controller connected to a Personal Computer and a Fibaro controller FGRGBWM-441. Operation of the system is controlled by software written in C++ using OpenZWave library. Some metrological aspects of the system are evaluated: accuracy, linearity, resolution and frequency of voltage measurements.

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  • Deep learning based thermal image segmentation for laboratory animals tracking

    Publikacja

    Automated systems for behaviour classification of laboratory animals are an attractive alternative to manual scoring. However, the proper animals separation and tracking, especially when they are in close contact, is the bottleneck of the behaviour analysis systems. In this paper, we propose a method for the segmentation of thermal images of laboratory rats that are in close contact during social behaviour tests. For this, we are...

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  • Electronic structure of TbBa2Cu3O7

    W pracy wykonano obliczenia kwantowomechaniczne struktury elektronowej hipotetycznego materiału TbBa2Cu3O7 (Dy123) metodą FP-LAPW (full potential - linearized augmented plane wave) w ramach formalizmu DFT (density functional theory) stosując przybliżenie GGA (generalized gradient approximation). Ze względu na silne oddziaływania korelacyjne elektronów 4f w atomie Tb zastosowano dodatkowo poprawkę kulombowską U w ramach modelu...

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  • Electronic structure and charge distribution in DyBa2Cu3O7: The ab initio approach

    W pracy wykonano obliczenia kwantowomechaniczne struktury elektronowej nadprzewodzącego materiału DyBa2Cu3O7 (Dy123) metodą FP-LAPW (full potential - linearized augmented plane wave) w ramach formalizmu DFT (density functional theory) stosując przybliżenie GGA (generalized gradient approximation). Ze względu na silne oddziaływania korelacyjne elektronów 4f w atomie Dy zastosowano dodatkowo poprawkę kulombowską U w ramach modelu...

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  • Highly Miniaturized Self-Diplexed U-Shaped Slot Antenna Based on Shielded QMSIW

    Publikacja

    - IEEE Access - Rok 2021

    This article presents an efficient yet simple design approach to highly miniaturized cavity-backed self-diplexing antenna (SDA) with high-isolation. The structure employs a shielded quarter-mode substrate integrated waveguide (QMSIW). Two U-shaped slots are engraved on the top conducting plane, which realize two frequency bands and significant size reduction. The slots are excited by two independent 50Ω orthogonal feed-lines to...

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  • Charge Distribution and Hyperfine Interactions in GdBa2Cu3O7 from First Principles

    Publikacja

    - Rok 2012

    W rozdziale przedstawiono wyniki obliczeń "z zasad pierwszych" (''ab initio'') struktury elektronowej, rozkładu ładunku i struktury nadsubtelnej, w szczególności gradientu pola elektrycznego (EFG) i składnika kontaktowego pola nadsubtelnego (HFF), nadprzewodnika wysokotemperaturowego o wzorze GdBa2Cu3O7 (Gd123). Do obliczeń wykorzystano metodę FP-LAPW (full-potential linearized augmented plane wave). Efekty związane z oddziaływaniami...

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  • Segmentation-Based BI-RADS ensemble classification of breast tumours in ultrasound images

    Publikacja
    • M. Bobowicz
    • M. Badocha
    • K. Gwozdziewicz
    • M. Rygusik
    • P. Kalinowska
    • E. Szurowska
    • T. Dziubich

    - INTERNATIONAL JOURNAL OF MEDICAL INFORMATICS - Rok 2024

    Background: The development of computer-aided diagnosis systems in breast cancer imaging is exponential. Since 2016, 81 papers have described the automated segmentation of breast lesions in ultrasound images using arti- ficial intelligence. However, only two papers have dealt with complex BI-RADS classifications. Purpose: This study addresses the automatic classification of breast lesions into binary classes (benign vs. ma- lignant)...

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