Browsing by Subject "SVM"

Now showing 1 - 20 of 23

Access status: Restricted ,
Agent based distributed classification system
(Data obrony: 2019-06-28) Latosiński, Waldemar
Wydział Elektrotechniki, Automatyki, Informatyki i Inżynierii Biomedycznej
Access status: Open Access ,
Applying Hunger Game Search (HGS) for selecting significant blood indicators for early prediction of ICU COVID-19 severity
(Wydawnictwa AGH, 2023) Sayed, Safynaz AbdEl-Fattah; ElKorany, Abeer; Sayed, Sabah
This paper introduces an early prognostic model for attempting to predict the severity of patients for ICU admission and detect the most significant features that affect the prediction process using clinical blood data. The proposed model predicts ICU admission for high-severity patients during the first two hours of hospital admission, which would help assist clinicians in decision-making and enable the efficient use of hospital resources. The Hunger Game search (HGS) meta-heuristic algorithm and a support vector machine (SVM) have been integrated to build the proposed prediction model. Furthermore, these have been used for selecting the most informative features from blood test data. Experiments have shown that using HGS for selecting features with the SVM classifier achieved excellent results as compared with four other meta-heuristic algorithms. The model that used the features that were selected by the HGS algorithm accomplished the topmost results (98.6 and 96.5%) for the best and mean accuracy, respectively, as compared to using all of the features that were selected by other popular optimization algorithms.
Access status: Restricted ,
Automatyczne rozpoznawanie tablic rejestracyjnych
(Data obrony: 2017-01-19) Zygmunt, Michał
Wydział Elektrotechniki, Automatyki, Informatyki i Inżynierii Biomedycznej
Access status: Restricted ,
Elektroniczny wizjer z funkcją rozpoznawania twarzy oparty na platformie Raspberry Pi i aplikacji webowej.
(Data obrony: 2019-12-10) Balicki, Dawid
Wydział Elektrotechniki, Automatyki, Informatyki i Inżynierii Biomedycznej
Access status: Open Access ,
High-Resolution Lithology Detection Using Sentinel-2A, ALOS PRISM L1B Images, and Support-Vector Machines in Tagragra d’Akka Inlier of Western Anti-Atlas, Morocco
(Wydawnictwa AGH, 2025) Hammoud, Yassine; Allali, Youssef; Saadane, Abderrahim
Geological mapping faces substantial challenges due to inaccessible terrains, labor-intensive field methods, and potential interpretative errors. This study proposes an innovative approach that leverages automatic lithology classification using multispectral Sentinel-2A (10 m) and high-resolution panchromatic ALOS PRISM L1B (2.5 m) images. Applied to the Tagragra d’Akka inlier of the Anti-Atlas region, the methodology enhances spatial resolution through pansharpening, followed by unsupervised segmentation. The segmented images are classified using support vector machines (SVMs) (supervised learning algorithms) to distinguish the lithological units. Achieving an 86% overall accuracy and an 84% kappa coefficient, the approach demonstrated robust performance and surpassed conventional techniques. The integration of machine learning and remote sensing offers a promising frontier for geological mapping – particularly in regions like the Tagragra d’Akka inlier. This study marks a significant advancement in automating lithological mapping, with implications for geological research, resource management, and hazard assessment. Automated techniques in geological cartography significantly enhance mapping accuracy and efficiency. Future studies should explore additional data sources and machine-learning algorithms to refine lithological classification and validate these methods across diverse geological settings.
Access status: Restricted ,
Implementacja algorytmu Computer Vision (CV) do wideo-detekcji ruchu pieszych i rowerzystów
(Data obrony: 2017-01-26) Sadlak, Patrick; Kwaśnicki, Marcin
Wydział Informatyki, Elektroniki i Telekomunikacji
Access status: Restricted ,
Implementacja sprzętowa wieloskalowej detekcji obiektów z wykorzystaniem algorytmu HOG+SVM
(Data obrony: 2018-01-22) Wąsala, Mateusz
Wydział Elektrotechniki, Automatyki, Informatyki i Inżynierii Biomedycznej
Access status: Restricted ,
Implementacja sprzętowa wieloskalowej detekcji obiektów z wykorzystaniem algorytmu HOG+SVM dla strumienia wideo o rozdzielczości 4K
(Data obrony: 2019-09-05) Wąsala, Mateusz
Wydział Elektrotechniki, Automatyki, Informatyki i Inżynierii Biomedycznej
Access status: Restricted ,
Klasyfikacja dokumentów przy użyciu sieci Kohonena i redukcja wymiarowości przestrzeni wektorowej z wykorzystaniem algorytmu scatter
(Data obrony: 2019-09-19) Domański, Karol
Wydział Inżynierii Metali i Informatyki Przemysłowej
Access status: Open Access ,
Machine-learning methods for assessing dynamic resistance of existing bridge structures subjected to mining tremors
(Wydawnictwa AGH, 2018) Rusek, Janusz
This paper demonstrates the results of research studies aimed at creating a model that allows to determine the resistance of existing bridge structures to the impact of mining tremors. A database (created by the author of this article) of the dynamic resistance of reinforced concrete bridge structures subjected to seismic excitations commonly occurring in the Legnica-Głogów Copper District (LGOM) formed the basis for the analysis. The dynamic resistance of each structure contained in the database was expressed as the limit values of the acceleration of ground vibrations that may be carried by a given structure without compromising its safety. The study was carried out using the Support Vector Machine (SVM) method in a Support Vector Regression (SVR) approach as well as an Artificial Neural Network (ANN). The models were compared in terms of the quality of the predictions and generalization of the acquired knowledge. This allows to select the most-effective method in evaluating the dynamic resistance of existing bridge structures.
Access status: Restricted ,
Metody uczenia maszynowego w prognozowaniu niedoszacowania pierwszych ofert publicznych
(Data obrony: 2020-07-16) Małkus, Bartłomiej
Wydział Informatyki, Elektroniki i Telekomunikacji
Access status: Open Access ,
Modelowanie i symulacja wybranych parametrów medycznych dla przypadków z niewydolnością oddechową
(2004-06-24) (Data obrony: 2008) Wais, Piotr Jan
Wydział Elektrotechniki, Automatyki, Informatyki i Elektroniki
The topic of this dissertation is modelling and simulation of chosen medical parameters related to the infants respiratory insufficiency. This issue is an important problem for patients admitted for ward hospitalization on the second day after birth due to the respiratory insufficiency. For modelling and simulation of insufficiency states computational intelligence tools were used. First issue is related to the modelling of predicted insufficiency states for the patient. These states are generated by the method based on artificial immune system algorithm. Second issue presented in the dissertation is a method of event classification. This method is known in literature as Support Vector Machine (SVM) and is used for classification of medical parameters, which are then used in prediction of mortality rate for patients with respiratory insufficiency.
Access status: Open Access ,
Neural network and artificial immune algorithms for the classification of medical data series
(Wydawnictwa AGH, 2012) Wajs, Wiesław
Dla rozpoznawania przypadków chorobowych, które są opisane numerycznymi danymi wykorzystano metody sztucznej inteligencji. W pracy wykorzystano dwie metody: metodę sztucznych sieci neuronowych oraz metodę sztucznych sieci immunologicznych. Przedstawiono wyniki uzyskane tymi metodami w odniesieniu do przypadków dysplazji oskrzelowo płucnej dla dzieci, których waga była poniżej 1500 g.
Access status: Restricted ,
Przewidywanie wyników biopsji raka piersi z wykorzystaniem metod uczenia maszynowego
(Data obrony: 2018-01-24) Tomczyk, Marta
Wydział Elektrotechniki, Automatyki, Informatyki i Inżynierii Biomedycznej
Access status: Open Access ,
Satellite data based abundance mapping of mafic and ultramafic rocks in Mettupalayam, Tamil Nadu, India
(Wydawnictwa AGH, 2021) Libeesh, Nharakkat Kalarikkal; Arivazhagan, Sundaram
The mafic and ultramafic rocks of Mettupalayam belong to the southern granulite terrain of India, which is concomitant with vital economic resources. The advantage of Advanced Spaceborne Thermal Emission and Reflectance Radiometer (ASTER) data for mapping the litho units are exploited well here for differentiating the rock units with the aid of band combination (1, 3, 6), principal component analysis (5, 1, 6) and band ratioed band combination (2/3, 3/2, 1/5 and (9–8)/1, (8–6)/2, and (9–6)/3). As part of the field study, the collection of samples and ground control points were carried out and in addition to that, the generation of laboratory reflectance spectra for samples was achieved. The Spectral Angle Mapper (SAM) and Support Vector Machine (SVM) were performed using ASTER data with the aid of spectra obtained from the laboratory conditions to demarcate the abundance of mafic and ultramafic rocks of the area. The XRF method was used to retrieve the major oxides of the field-collected samples and the spectral absorption characters are validated with it. The results show a vibrant interpretation of the litho units.
Access status: Restricted ,
Sprzętowo-programowy system detekcji obiektów na podstawie fuzji danych z czujnika LIDAR oraz kamery
(Data obrony: 2019-01-31) Lis, Konrad
Wydział Elektrotechniki, Automatyki, Informatyki i Inżynierii Biomedycznej
Access status: Restricted ,
Wpływ doboru parametrów maszyny wektorów nośnych (Support Vector Machine) na jakość klasyfikacji binarnej
(Data obrony: 2017-01-26) Kapusta, Grzegorz
Wydział Elektrotechniki, Automatyki, Informatyki i Inżynierii Biomedycznej
Access status: Restricted ,
Wykorzystanie metody wektorów nośnych w analizie danych geofizycznych.
(Data obrony: 2020-02-04) Knap, Natalia
Wydział Geologii, Geofizyki i Ochrony Środowiska
Access status: Restricted ,
Wykorzystanie modeli uczenia maszynowego do weryfikacji błędów w oprogramowaniu
(Data obrony: 2020-07-10) Martyka, Franciszek
Wydział Zarządzania
Access status: Restricted ,
Wykrywanie anomalii w dużych zbiorach danych za pomocą sieci neuronowych
(Data obrony: 2018-01-23) Piwowarczyk, Wojciech
Wydział Informatyki, Elektroniki i Telekomunikacji