Výsledky vyhledávání - "Agnieszka Siwocha"

Combined YOLOv5 and HRNet for High Accuracy 2D Keypoint and Human Pose Estimation

Autor: Hung-Cuong Nguyen, Thi-Hao Nguyen, Jakub Nowak, Aleksander Byrski, Agnieszka Siwocha, Van-Hung Le

Publikováno v: Journal of Artificial Intelligence and Soft Computing Research. 12:281-298

Two-dimensional human pose estimation has been widely applied in real-world applications such as sports analysis, medical fall detection, human-robot interaction, with many positive results obtained utilizing Convolutional Neural Networks (CNNs). Li

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::5b79a6393e39835a2a0ac2b0e97f0687
https://doi.org/10.2478/jaiscr-2022-0019

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Towards a Very Fast Feedforward Multilayer Neural Networks Training Algorithm

Autor: Jarosław Bilski, Bartosz Kowalczyk, Marek Kisiel-Dorohinicki, Agnieszka Siwocha, Jacek Żurada

Publikováno v: Journal of Artificial Intelligence and Soft Computing Research. 12:181-195

**This paper presents a novel fast algorithm for feedforward neural networks training. It is based on the Recursive Least Squares (RLS) method commonly used for designing adaptive filters. Besides, it utilizes two techniques of linear algebra, namely

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::bf8c631f024f68245faa882d99917039
https://doi.org/10.2478/jaiscr-2022-0012

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Handwritten Word Recognition Using Fuzzy Matching Degrees

Autor: Agnieszka Siwocha, Janusz T. Starczewski, Justyna Fijałkowska, Michal R. Wróbel, Christian Napoli

Publikováno v: Journal of Artificial Intelligence and Soft Computing Research. 11:229-242

Handwritten text recognition systems interpret the scanned script images as text composed of letters. In this paper, efficient offline methods using fuzzy degrees, as well as interval fuzzy degrees of type-2, are proposed to recognize letters beforeh

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::160409693360fafefd4825c54f6e6744
https://doi.org/10.2478/jaiscr-2021-0014

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Detecting Visual Objects by Edge Crawling

Autor: Agnieszka Siwocha, Rafał Grycuk, Wei Wei, Adam Wojciechowski

Publikováno v: Journal of Artificial Intelligence and Soft Computing Research. 10:223-237

Content-based image retrieval methods develop rapidly with a growing scale of image repositories. They are usually based on comparing and indexing some image features. We developed a new algorithm for finding objects in images by traversing their edg

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::09dba598241d235f174fa053d413a1bf
https://doi.org/10.2478/jaiscr-2020-0015

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Efficient image retrieval by fuzzy rules from boosting and metaheuristic

Autor: Marcin Korytkowski, Rafal A. Angryk, Agnieszka Siwocha, Roman Senkerik, Magdalena Scherer, Mirosław Kordos

Publikováno v: Journal of Artificial Intelligence and Soft Computing Research

Fast content-based image retrieval is still a challenge for computer systems. We present a novel method aimed at classifying images by fuzzy rules and local image features. The fuzzy rule base is generated in the first stage by a boosting procedure.

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6c15fb5166e81762aa33d3272cb246d5
http://publikace.k.utb.cz/handle/10563/1009514

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Microscopic Sample Segmentation by Fully Convolutional Network for Parasite Detection

Autor: Patryk Najgebauer, Leszek Rutkowski, Agnieszka Siwocha, Rafał Scherer, Rafał Grycuk

Publikováno v: Artificial Intelligence and Soft Computing ISBN: 9783030209117
ICAISC (1)

This paper describes a method of pixel-level segmentation applied to parasite detection. Parasite diseases in most cases are detected by microscopic samples examination or by ELISA blood tests. The microscopic methods are less invasive and often used

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::54801431350a25a02ddf5d3345d35536
https://doi.org/10.1007/978-3-030-20912-4_16

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Random Forests for Profiling Computer Network Users

Autor: Marcin Korytkowski, Rafał Scherer, Jakub Nowak, Agnieszka Siwocha, Robert K. Nowicki

Publikováno v: Artificial Intelligence and Soft Computing ISBN: 9783319912615
ICAISC (2)

In this paper, we present a novel system to detect abnormal behaviour of computer network users based on features of web pages which were requested by a user (e.g. URL address, URL category, the day of week or time when the web page was visited). The

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::5e93e1a9772c87c430a110e34d2add6e
https://doi.org/10.1007/978-3-319-91262-2_64

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Architecture of Database Index for Content-Based Image Retrieval Systems

Autor: Rafał Scherer, Rafał Grycuk, Agnieszka Siwocha, Patryk Najgebauer

Publikováno v: Artificial Intelligence and Soft Computing ISBN: 9783319912615
ICAISC (2)

In this paper, we present a novel database index architecture for retrieving images. Effective storing, browsing and searching collections of images is one of the most important challenges of computer science. The design of architecture for storing s

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::9f6f636c3a6359f766f8d23f6df97642
https://doi.org/10.1007/978-3-319-91262-2_4

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