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EN
The suspension system in an automobile is essential for comfort and control. Implementing a monitoring system is crucial to ensure proper function, prevent accidents, maintain performance, and reduce both downtime and costs. Traditionally, diagnosing faults in suspension systems has relied on specialized setups and vibration analysis. The conventional approach typically involves either wavelet analysis or a machine learning approach. While these methods are effective, they often demand specialized expertise and time consumable. Alternatively, using deep learning for suspension system fault diagnosis enables faster and more precise real-time fault detection. This study explores the use of vision transformers as an innovative approach to fault diagnosis in suspension systems, utilizing spectrogram images. The process involves extracting spectrogram images from vibration signals, which serve as inputs for the vision transformer model. The test results demonstrate that the proposed fault diagnosis system achieves an impressive accuracy rate of 98.12% in identifying faults.
PL
W artykule przedstawiono algorytm dla komputerowej wizualizacji w czasie rzeczywistym sceny nocnej złożonej z punktów świetlnych, widzianej przez pilota samolotu.
EN
The article presents a computer algorithm for real-time visualization of a night scene composed of points of light, as seen by a pilot of the aircraft.
3
PL
W artykule przedstawiono przekształcenia matematyczne dla komputerowej wizualizacji w czasie rzeczywistym sceny widzianej przez obserwatora. Ponieważ nie jesteśmy w stanie generować realnych obrazów pola widzenia w czasie rzeczywistym, dlatego dąży się do kompromisu między złożonością modelu a postacią generowanych obrazów.
EN
This paper presents mathematical transformations for computer real-time visualization of the scene as seen by the observer. Since we are not able to generate realistic images of visual field in real time, so the aim is to reach a compromise between the complexity of the model and the form of generated images.
4
Content available remote Modelowanie struktur 2D i 3D a ich odwzorowywanie w czasie rzeczywistym
PL
Obecnie nie jesteśmy w stanie generować w czasie rzeczywistym realnych obrazów pola widzenia. Dotyczy to zwłaszcza obiektów 3D. Dlatego dąży sie do kompromisu między złożnością modelu a postacią generowanych obrazów. Zadowalajace rezultaty moe dac symulacja widoków obiektów majacych istotne znaczenie i dostosowanie do nich poziomu szczegółowosci obrazu.
EN
Currently we are not able to generate real-time images of real vision. This applies especially to 3D objects. Therefore, the aim is to reach a compromise between the complexity of the model and the form of generated images. Satisfactory results can be achieved by simulating views of significant objects and adjusting the level of detail in the picture.
5
Content available remote Aspekty odwzorowania terenu dla potrzeb symulacji komputerowej
PL
Jednym z podstawowych zadań matematycznego odwzorowania jest sformułowanie opisu procesów zachodzących w rzeczywistych warunkach i w modelowanym układzie. Obecnie nie jesteśmy w stanie generować w czasie rzeczywistym realnych obrazów pola widzenia. Symulacja widoków obiektów mających istotne znaczenie i dostosowanie do nich poziomu szczegółowości obrazu może dać zadowalające rezultaty.
EN
One of the basic tasks of mathematical mapping is formulating the description of processes occurring in real conditions or in a model. Currently we are not able to generate real fields of view in real time. Simulation of significant objects and adjusting the level of details to images might give satisfied results.
EN
This paper presents an approach to the IFS inverse problem based on evolutionary computations. Having a bitmap image, we look for a set of functions that can reproduce a good approximation of a given image. A method using a variable number of mappings is proposed. A number of different crossover operators is described and tested. The possibility of enriching evolutionary algorithms by a specific type mechanism characteristic for replication of influenza viruses is discussed. The genetic material of the influenza type A virus consists of eight separate segments. In some types of tasks, such a structure of a genome can be more adequate than representation that consists of one sequence only. If influenza virus strains infect the same cell, then their RNA segments can mix freely, producing progeny viruses which represents the reasortment mechanism. Furthermore, mistakes leading to new mutations are common. The structure of problems for which such viral reproduction mechanisms can be effective are analyzed. The paper ends with some experimental results showing the images we were able to generate with the proposed method. The preliminary experimental results suggest that the introduction of the reasortment operator results in achieving satisfactory images in a smaller number of generations.
EN
Image generation has been proposed for many different tasks in the literature, from physics events visualization to the purpose of "art for art's sake". In this paper a new approach to computer image generation is presented: the method creates new images by randomizing the decompression process, starting from a compressed representation of an image by Iterate Function Systems. Petri Nets are employed both for modeling the decompression process and for inserting a randomization component in it. A second method proposed in this work directly translates the evolution of a Petri Net into a graphic output. Experimental results are given, showing different class of images generated by the two methods.
8
Content available remote Image representation and generation by ifs and Petri nets
EN
Image generation has been proposed for many different tasks in the literature, from physics events visualization to large databases creation, from creative design to the purpose of "art for art's sake". In this paper a new approach to computer image generation is presented: the method creates new images by randomizing the decompression process, starting from a compressed representation of an image by Iterate Function Systems. Petri Nets are employed both for modeling the decompression process and for inserting a randomization component in it. A second method proposed in this work directly translates the evolution of a Petri Net into a graphic output. Experimental results are given, showing different class of images generated by the two methods.
9
Content available remote Image generation by Petri nets
EN
This paper presents a new approach to computer image generation. The basic idea is to translate the evolution of a Petri net into a graphic output. In particular, we focus on three methods for image generation which exhibit a certain analogy whit fractals. Some experimental results are reported together whit a brief investigation on the relationships between generated images and thier corresponding Petri nets.
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