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Wyniki wyszukiwania dla: GRAPH NEURAL NETWORK
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Artificial Neural Networks in Engineering Conference
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European Symposium on Artificial Neural Networks
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IEEE International Conference on Neural Networks
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International Conference on Artificial Neural Networks
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International Conference on Neural Information Processing
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User Orientation Detection in Relation to Antenna Geometry in Ultra-Wideband Wireless Body Area Networks Using Deep Learning
PublikacjaIn this paper, the issue of detecting a user’s position in relation to the antenna geometry in ultra-wideband (UWB) off-body wireless body area network (WBAN) communication using deep learning methods is presented. To measure the impulse response of the channel, a measurement stand consisting of EVB1000 devices and DW1000 radio modules was developed and indoor static measurement scenarios were performed. It was proven that for...
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THE ROLE OF INFERENCE IN MOBILE MEDICAL APPLICATION DESIGN
PublikacjaIn the early 21st century, artificial intelligence began to be used to process medical information. However, before this happened, predictive models used in healthcare could only consider a limited number of variables, and only in properly structured and organised medical data. Today, advanced tools based on machine learning techniques - which, using artificial neural networks, can explore extremely complex relationships - and...
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Dataset of non-isomorphic graphs of the coloring types (K3,Km-e;n), 2<m<7, 1<n<R(K3,Km-e).
Dane BadawczeFor K3 and Km-e graphs, a coloring type (K3,Km-e;n) is such an edge coloring of the full Kn graph, which does not have the K3 subgraph in the first color (representing by no edges in the graph) or the Km-e subgraph in the second color (representing by edges in the graph). Km-e means the full Km graph with one edge removed.The Ramsey number R(K3,Km-e)...
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CNN Architectures for Human Pose Estimation from a Very Low Resolution Depth Image
PublikacjaThe paper is dedicated to proposing and evaluating a number of convolutional neural network architectures for calculating a multiple regression on 3D coordinates of human body joints tracked in a single low resolution depth image. The main challenge was to obtain a high precision in case of a noisy and coarse scan of the body, as observed by a depth sensor from a large distance. The regression network was expected to reason about...
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Comparison of image pre-processing methods in liver segmentation task
PublikacjaAutomatic 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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Dynamic F-free Coloring of Graphs
PublikacjaA problem of graph F-free coloring consists in partitioning the vertex set of a graph such that none of the resulting sets induces a graph containing a fixed graph F as an induced subgraph. In this paper we consider dynamic F-free coloring in which, similarly as in online coloring, the graph to be colored is not known in advance; it is gradually revealed to the coloring algorithm that has to color each vertex upon request as well...
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Video of LEGO bricks on conveyor belt - Special Brics
Dane BadawczeThe set contains videos of LEGO bricks (special bricks, with additional connectors etc.) moving on a white conveyor belt. The videos were prepared for training neural network for recognition of LEGO bricks. The bricks were separated as much as possible and in most cases they should not overlap. The images were taken from different sides by stationary...
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Video of LEGO bricks on conveyor belt - Wide Brics
Dane BadawczeThe set contains videos of LEGO bricks (wide bricks, with each side having more than 1 stud) moving on a white conveyor belt. The videos were prepared for training neural network for recognition of LEGO bricks. The bricks were separated as much as possible and in most cases they should not overlap. The images were taken from different sides by stationary...
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Video of LEGO bricks on conveyor belt - minifigures, animals, plants and accessories
Dane BadawczeThe set contains videos of LEGO bricks (minifigures, animals, plants and accessories) moving on a white conveyor belt. The images were prepared for training neural network for recognition of LEGO bricks. The bricks were separated as much as possible and in most cases they should not overlap. The images were taken from different sides by stationary camera...
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Video of LEGO bricks on conveyor belt - Narrow Brics
Dane BadawczeThe set contains videos of LEGO bricks (narrow bricks, with on side no wider than 1 stud) moving on a white conveyor belt. The videos were prepared for training neural network for recognition of LEGO bricks. The bricks were separated as much as possible and in most cases they should not overlap. The images were taken from different sides by stationary...
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Dataset of non-isomorphic graphs being coloring types (K4-e,Km-e;n), 2<m<7, 1<n<R(K4-e,Km-e)
Dane BadawczeFor K4-e and Km-e graphs, the type coloring (K4-e,Km-e;n) is such an edge coloring of the full Kn graph, which does not have the K4-e subgraph in the first color (no edge in the graph) or the Km-e subgraph in the second color (exists edge in the graph). Km-e means the full Km graph with one edge removed.The Ramsey number R(K4-e,Km-e) is the smallest...
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Joanna Czerska dr inż.
OsobyJoanna Czerska jestem człowiekiem, którego misją i pasją jest rozwój ludzi i organizacji. Moje motto to: „Nie ma takiej fantazji, której wola i rozum ludzki nie zdołałby przekształcić w rzeczywistość.” William Shakespeare W życiu kieruję się wartościami szacunku, pracy zespołowej i pozytywnego nastawienia. To one mnie definiują i decydują o tym jakim jest człowiekiem.Moja przygoda z Lean rozpoczęła się, podczas pisania pracy...
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On proper (1,2)‐dominating sets in graphs
PublikacjaIn 2008, Hedetniemi et al. introduced the concept of (1,)-domination and obtained some interesting results for (1,2) -domination. Obviously every (1,1) -dominating set of a graph (known as 2-dominating set) is (1,2) -dominating; to distinguish these concepts, we define a proper (1,2) -dominating set of a graph as follows: a subset is a proper (1,2) -dominating set of a graph if is (1,2) -dominating and it is not a (1,1) -dominating...
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Dataset of non-isomorphic graphs of the coloring types (K3,Km;n), 2<m<7, 1<n<R(3,m)
Dane BadawczeFor K3 and Km graphs, a coloring type (K3,Km;n) is such an edge coloring of the full Kn graph, which does not have the K3 subgraph in the first color (representing by no edges in the graph) or the Km subgraph in the second color (representing by edges in the graph).The Ramsey number R(3,m) is the smallest natural number n such that for any edge coloring...
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Deep Learning Basics 2023/24
Kursy OnlineA 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.