Autor: Scherer, M. - Katalog OPAC zbiorów

Skocz do pozycji: 1.

Tytuł:: Orthopedic diagnostics with ensembles of learning systems
Autorzy:: Szarek, A.
Korytkowski, M.
Rutkowski, L.
Scherer, R.
Szyprowski, J.
Powiązania:: https://bibliotekanauki.pl/articles/99251.pdf
Data publikacji:: 2012
Wydawca:: Politechnika Śląska. Katedra Biomechatroniki
Tematy:: hip joint
prosthesis
assessing orthopaedic data
classifier
staw biodrowy
proteza
ocena danych ortopedycznych
klasyfikator
Źródło:: Aktualne Problemy Biomechaniki; 2012, 6; 141-146
1898-763X
Pojawia się w:: Aktualne Problemy Biomechaniki
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 2.

Tytuł:: New image descriptor from edge detector and blob extractor
Autorzy:: Grycuk, R.
Scherer, R.
Gabryel, M.
Powiązania:: https://bibliotekanauki.pl/articles/122401.pdf
Data publikacji:: 2015
Wydawca:: Politechnika Częstochowska. Wydawnictwo Politechniki Częstochowskiej
Tematy:: image description
content-based image retrieval (CBIR)
edge detection
blob extraction
blob detection
opis obrazu
wyszukiwanie na podstawie zawartości
CBIR
wykrywanie krawędzi
Opis:: In this paper we present a novel approach for image description. The method is based on two well-known algorithms: edge detection and blob extraction. In the edge detection step we use the Canny detector. Our method provides a mathematical description of each object in the input image. On the output of the presented algorithm we obtain a histogram, which can be used in various fields of computer vision. In this paper we applied it in the content-based image retrieval system. The simulations proved the effectiveness of our method.
Źródło:: Journal of Applied Mathematics and Computational Mechanics; 2015, 14, 4; 31-39
2299-9965
Pojawia się w:: Journal of Applied Mathematics and Computational Mechanics
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 3.

Tytuł:: Management of reverse logistics processes with Microsoft Dynamics NAV
Autorzy:: Scherer, M.
Powiązania:: https://bibliotekanauki.pl/articles/111947.pdf
Data publikacji:: 2017
Wydawca:: Stowarzyszenie Menedżerów Jakości i Produkcji
Tematy:: reverse logistics
ERP
logistyka zwrotna
system ERP
Opis:: Appropriate management of waste streams is a very important part of business operations as it is reflected in the reduction in the flow and use of materials. It also minimizes negative impact on the environment. The article discusses the capabilities of Microsoft Dynamics NAV in the management of reverse logistics processes. We also developed a system supporting reverse logistics as a module for Microsoft Dynamics NAV. It automatically counts waste dividing them into appropriate groups. At the time of writing there was no direct support for waste management in the Dynamics NAV system.
Źródło:: Production Engineering Archives; 2017, 15; 11-14
2353-5156
2353-7779
Pojawia się w:: Production Engineering Archives
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 4.

Tytuł:: Waste flows management by their prediction in a production company
Autorzy:: Scherer, M.
Powiązania:: https://bibliotekanauki.pl/articles/122413.pdf
Data publikacji:: 2017
Wydawca:: Politechnika Częstochowska. Wydawnictwo Politechniki Częstochowskiej
Tematy:: reverse logistics
artificial intelligence
logistyka zwrotna
sztuczna inteligencja
systemy neuronowo-rozmyte
Opis:: In this paper we apply neuro-fuzzy systems to predict waste production in a company. Waste is produced by companies at every phase of their business, e.g. at the stage of supply, production and distribution. We used data on the production waste of one of the typical Polish manufacturing companies operating in the automotive industry. We predicted monthly waste production by data-driven learning of neuro-fuzzy systems. Neuro-fuzzy systems share with artificial neural-networks the ability to learn from data and the interpretability with fuzzy systems. In the experiments we achieved a high rate of prediction.
Źródło:: Journal of Applied Mathematics and Computational Mechanics; 2017, 16, 2; 135-144
2299-9965
Pojawia się w:: Journal of Applied Mathematics and Computational Mechanics
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 5.

Tytuł:: Multi-layer neural networks for sales forecasting
Autorzy:: Scherer, M.
Powiązania:: https://bibliotekanauki.pl/articles/122611.pdf
Data publikacji:: 2018
Wydawca:: Politechnika Częstochowska. Wydawnictwo Politechniki Częstochowskiej
Tematy:: data forecasting
machine learning
artificial neural networks
sztuczna sieć neuronowa
uczenie maszynowe
systemy neuro-rozmyte
Opis:: Predicting business operations on the basis of previous events plays an important role in managing a company. In the paper, we predict monthly sales volume of a textile warehouse by mathematical tools. To this end we use a feedforward artificial neural network trained on past data. The network predicted the volume with high accuracy. For the examined company, such prediction is very important as nearly the entire range of products is imported from different countries and the goods have to be ordered in advance.
Źródło:: Journal of Applied Mathematics and Computational Mechanics; 2018, 17, 1; 61-68
2299-9965
Pojawia się w:: Journal of Applied Mathematics and Computational Mechanics
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 6.

Tytuł:: Efficient image retrieval by fuzzy rules from boosting and metaheuristic
Autorzy:: Korytkowski, Marcin
Senkerik, Roman
Scherer, Magdalena M.
Angryk, Rafal A.
Kordos, Miroslaw
Siwocha, Agnieszka
Powiązania:: https://bibliotekanauki.pl/articles/91856.pdf
Data publikacji:: 2020
Wydawca:: Społeczna Akademia Nauk w Łodzi. Polskie Towarzystwo Sieci Neuronowych
Tematy:: image retrieval
fuzzy rules
local image features
pobieranie obrazu
lokalne funkcje obrazu
Opis:: 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. Boosting meta-learning is used to find the most representative local features. We briefly explore the utilization of metaheuristic algorithms for the various tasks of fuzzy systems optimization. We also provide a comprehensive description of the current best-performing DISH algorithm, which represents a powerful version of the differential evolution algorithm with effective embedded mechanisms for stronger exploration and preservation of the population diversity, designed for higher dimensional and complex optimization tasks. The algorithm is used to fine-tune the fuzzy rule base. The fuzzy rules can also be used to create a database index to retrieve images similar to the query image fast. The proposed approach is tested on a state-of-the-art image dataset and compared with the bag-of-features image representation model combined with the Support Vector Machine classification. The novel method gives a better classification accuracy, and the time of the training and testing process is significantly shorter.
Źródło:: Journal of Artificial Intelligence and Soft Computing Research; 2020, 10, 1; 57-69
2083-2567
2449-6499
Pojawia się w:: Journal of Artificial Intelligence and Soft Computing Research
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 7.

Tytuł:: Fast image index for database management engines
Autorzy:: Grycuk, Rafał
Najgebauer, Patryk
Kordos, Miroslaw
Scherer, Magdalena M.
Marchlewska, Alina
Powiązania:: https://bibliotekanauki.pl/articles/1837480.pdf
Data publikacji:: 2020
Wydawca:: Społeczna Akademia Nauk w Łodzi. Polskie Towarzystwo Sieci Neuronowych
Tematy:: image descriptor
content-based image retrieval
image indexing
Opis:: Large-scale image repositories are challenging to perform queries based on the content of the images. The paper proposes a novel, nested-dictionary data structure for indexing image local features. The method transforms image local feature vectors into two-level hashes and builds an index of the content of the images in the database. The algorithm can be used in database management systems. We implemented it with an example image descriptor and deployed in a relational database. We performed the experiments on two image large benchmark datasets.
Źródło:: Journal of Artificial Intelligence and Soft Computing Research; 2020, 10, 2; 113-123
2083-2567
2449-6499
Pojawia się w:: Journal of Artificial Intelligence and Soft Computing Research
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 8.

Tytuł:: A novel grid-based clustering algorithm
Autorzy:: Starczewski, Artur
Scherer, Magdalena M.
Książek, Wojciech
Dębski, Maciej
Wang, Lipo
Powiązania:: https://bibliotekanauki.pl/articles/2031101.pdf
Data publikacji:: 2021
Wydawca:: Społeczna Akademia Nauk w Łodzi. Polskie Towarzystwo Sieci Neuronowych
Tematy:: data mining
grid-based clustering
grid structure
Opis:: Data clustering is an important method used to discover naturally occurring structures in datasets. One of the most popular approaches is the grid-based concept of clustering algorithms. This kind of method is characterized by a fast processing time and it can also discover clusters of arbitrary shapes in datasets. These properties allow these methods to be used in many different applications. Researchers have created many versions of the clustering method using the grid-based approach. However, the key issue is the right choice of the number of grid cells. This paper proposes a novel grid-based algorithm which uses a method for an automatic determining of the number of grid cells. This method is based on the kdist function which computes the distance between each element of a dataset and its kth nearest neighbor. Experimental results have been obtained for several different datasets and they confirm a very good performance of the newly proposed method.
Źródło:: Journal of Artificial Intelligence and Soft Computing Research; 2021, 11, 4; 319-330
2083-2567
2449-6499
Pojawia się w:: Journal of Artificial Intelligence and Soft Computing Research
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 9.

Tytuł:: Decision making support system for managing advertisers by ad fraud detection
Autorzy:: Gabryel, Marcin
Scherer, Magdalena M.
Sułkowski, Łukasz
Damaševičius, Robertas
Powiązania:: https://bibliotekanauki.pl/articles/2031082.pdf
Data publikacji:: 2021
Wydawca:: Społeczna Akademia Nauk w Łodzi. Polskie Towarzystwo Sieci Neuronowych
Tematy:: lead management
feedforward neural networks
embedding
online marketing
Opis:: Efficient lead management allows substantially enhancing online channel marketing programs. In the paper, we classify website traffic into human- and bot-origin ones. We use feedforward neural networks with embedding layers. Moreover, we use one-hot encoding for categorical data. The data of mouse clicks come from seven large retail stores and the data of lead classification from three financial institutions. The data are collected by a JavaScript code embedded into HTML pages. The three proposed models achieved relatively high accuracy in detecting artificially generated traffic.
Źródło:: Journal of Artificial Intelligence and Soft Computing Research; 2021, 11, 4; 331--339
2083-2567
2449-6499
Pojawia się w:: Journal of Artificial Intelligence and Soft Computing Research
Dostawca treści:: Biblioteka Nauki

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