Magdalena Mazur-Milecka - Publikacje - MOST Wiedzy

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Rok 2024
  • A Mammography Data Management Application for Federated Learning
    Publikacja

    This study aimed to develop and assess an application designed to enhance the management of a local client database consisting of mammographic images with a focus on ensuring that images are suitably and uniformly prepared for federated learning applications. The application supports a comprehensive approach, starting with a versatile image-loading function that supports DICOM files from various medical imaging devices and settings....

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  • Artificial Intelligence in the Diagnosis of Onychomycosis—Literature Review
    Publikacja

    - Journal of Fungi - Rok 2024

    Onychomycosis is a common fungal nail infection that is difficult to diagnose due to its similarity to other nail conditions. Accurate identification is essential for effective treatment. The current gold standard methods include microscopic examination with potassium hydroxide, fungal cultures, and Periodic acid-Schiff biopsy staining. These conventional techniques, however, suffer from high turnover times, variable sensitivity,...

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  • Automated Parking Management for Urban Efficiency: A Comprehensive Approach
    Publikacja

    - Rok 2024

    Effective parking management is essential for ad-dressing the challenges of traffic congestion, city logistics, and air pollution in densely populated urban areas. This paper presents an algorithm designed to optimize parking management within city environments. The proposed system leverages deep learning models to accurately detect and classify street elements and events. Various algorithms, including automatic segmentation of...

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  • Enhancing Facial Palsy Treatment through Artificial Intelligence: From Diagnosis to Recovery Monitoring
    Publikacja

    The objective of this study is to develop and assess a mobile application that leverages artificial intelligence (AI) to support the rehabilitation of individuals with facial nerve paralysis. The application features two primary functionalities: assessing the paralysis severity and facilitating the monitoring of rehabilitation exercises. The AI algorithm employed for this purpose was Google's ML Kit “face-detection”. The classification...

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  • Evaluating the Use of Edge Device Towards Fall Detection in Smart City Environment
    Publikacja

    - Rok 2024

    This paper presents the development and preliminary testing of a fall detection algorithm that leverages OpenPose for real-time human pose estimation from video feeds. The system is designed to function optimally within a range of up to 7 meters from ground-level cameras, focusing exclusively on detected human silhouettes to enhance processing efficiency. The performance of the proposed approach was evaluated using accuracy values...

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  • Evaluating the Use of Edge Devices for Detection and Tracking of Vehicles in Smart City Environment
    Publikacja

    - Rok 2024

    This paper introduces a Smart City solution designed to run on edge devices, leveraging NVIDIA's DeepStream SDK for efficient urban surveillance. We evaluate five object-tracking approaches, using YOLO as the baseline detector and integrating three Nvidia DeepStream trackers: IOU, NvSORT, and NvDCF. Additionally, we propose a custom tracker based on Optical Flow and Kalman filtering. The presented approach combines advanced machine...

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  • Preeclampsia Risk Prediction Using Machine Learning Methods Trained on Synthetic Data
    Publikacja

    - Rok 2024

    This paper describes a research study that investigates the use of machine learning algorithms on synthetic data to classify the risk of developing preeclampsia by pregnant women. Synthetic datasets were generated based on parameter distributions from three real patient studies. Four models were compared: XGBoost, Support Vector Machine (SVM), Random Forest, and Explainable Boosting Machines (EBM). The study found that the XGBoost...

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Rok 2023
Rok 2022
Rok 2021
Rok 2020
  • Deep Instance Segmentation of Laboratory Animals in Thermal Images

    In this paper we focus on the role of deep instance segmentation of laboratory rodents in thermal images. Thermal imaging is very suitable to observe the behaviour of laboratory animals, especially in low light conditions. It is an non-intrusive method allowing to monitor the activity of animals and potentially observe some physiological changes expressed in dynamic thermal patterns. The analysis of the recorded sequence of thermal...

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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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Rok 2019
  • 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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  • Evaluation of Facial Pulse Signals Using Deep Neural Net Models
    Publikacja

    - Rok 2019

    The reliable measurement of the pulse rate using remote photoplethysmography (PPG) is very important for many medical applications. In this paper we present how deep neural networks (DNNs) models can be used in the problem of PPG signal classification and pulse rate estimation. In particular, we show that the DNN-based classification results correspond to parameters describing the PPG signals (e.g. peak energy in the frequency...

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Rok 2018
Rok 2017
Rok 2016
  • Thermal imaging in automatic rodent’s social behaviour analysis
    Publikacja

    - Rok 2016

    Laboratory rodent social behaviour analysis is an extremely important task for biological, medical and pharmacological researches. In this work thermal images features that facilitate analysis are presented. Methods to distinguish objects on the basis of thermal distribution are tested. Actions of grooming or biting one rodent by another - important social behaviour incidents - are clearly visible...

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Rok 2011
Rok 2010

wyświetlono 2868 razy