Wyniki wyszukiwania - BazTech

1

Creating see-around scenes using panorama stitching

Alferidah Saja, Alkhaldi Nora

Annals of Computer Science and Information Systems

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2019

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Vol. 18

293-–301

EN

Image stitching refers to the process of combining multiple images of the same scene to produce a single high-resolution image, known as panorama stitching. The aim of this paper is to produce a high-quality stitched panorama image with less computation time. This is achieved by proposing four combinations of algorithms. First combination includes FAST corner detector, Brute Force K-Nearest Neighbor (KNN) and Random Sample Consensus (RANSAC). Second combination includes FAST, Brute Force (KNN) and Progressive Sample Consensus (PROSAC). Third combination includes ORB, Brute Force (KNN) and RANSAC. Fourth combination contains ORB, Brute Force (KNN) and PROSAC. Next, each combination involves a calculation of Transformation Matrix. The results demonstrated that the fourth combination produced a panoramic image with the highest performance and better quality compared to other combinations. The processing time is reduced by 67% for the third combination and by 68% for the fourth combination compared to stat-of-the-art.

2

Prediction of mortality rates in heart failure patients with data mining methods

Bohacik J., Kambhampati C., Davis D. N., Cleland J. G. F.

Annales Universitatis Mariae Curie-Skłodowska. Sectio AI, Informatica

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2013

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Vol. 13, no. 1

7--16

EN

Heart failure is one of the severe diseases which menace the human health and affect millions of people. Half of all patients diagnosed with heart failure die within four years. For the purpose of avoiding life-threatening situations and minimizing the costs, it is important to predict mortality rates of heart failure patients. As part of a HEIF-5 project, a data mining study was conducted aiming specifically at extracting new knowledge from a group of patients suffering from heart failure and using it for prediction of mortality rates. The methodology of knowledge discovery in databases is analyzed within the framework of home telemonitoring. Several data mining methods such as a Bayesian network method, a decision tree method, a neural network method and a nearest neighbour method are employed. The accuracy for the data mining methods from the point of view of avoiding life-threatening situations and minimizing the costs is discussed. It seems that the decision tree method achieves the best accuracy results and is also interpretable for the clinicians.

3

RIONA: A New Classification System Combining Rule Induction and Instance-Based Learning

Góra G., Wojna A.

Fundamenta Informaticae

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2002

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Vol. 51, nr 4

369-390

EN

The article describes a method combining two widely-used empirical approaches to learning from examples: rule induction and instance-based learning. In our algorithm (RIONA) decision is predicted not on the basis of the whole support set of all rules matching a test case, but the support set restricted to a neighbourhood of a test case. The size of the optimal neighbourhood is automatically induced during the learning phase. The empirical study shows the interesting fact that it is enough to consider a small neighbourhood to achieve classification accuracy comparable to an algorithm considering the whole learning set. The combination of k-NN and a rule-based algorithm results in a significant acceleration of the algorithm using all minimal rules. Moreover, the presented classifier has high accuracy for both kinds of domains: more suitable for k-NN classifiers and more suitable for rule based classifiers.

4

Rozpoznawanie obrazów metodą minimalnoodległościową

Gajer M.

Kwartalnik Elektroniki i Telekomunikacji

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2000

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Vol. 46, nr 3

413-429

PL

W artykule omówiono sposób funkcjonowania systemu wizyjnego przeznaczonego do automatycznego rozpoznawania typów układów scalonych. System taki może znaleźć praktyczne zastosowanie na stanowiskach automatycznego montażu układów scalonych przez robota przemysłowego, bądź też może zostać wykorzystanny na stanowisku automatycznej kontroli jakości produkcji, gdzie zachodzi konieczność zapewnienia, że w danym miejscu został umieszczony układ scalony o pożądanym typie. W artykule opisano szczegółowo wszystkie operacje wykonywane w celu rozpoznania typu układu scalonego, takie jak : pozyskanie obrazu z kamery, przetworzenie wstępne obrazu, segmentacje obrazu, pomiar wartości cech opisujących rozpoznawane obiekty oraz wybór klasy przynależności rozpoznawanego obiektu. Jako metodę rozpoznawania wybrano metodę minimalnoodległościową, polegającą na poszukiwaniu najbliższego sąsiada w przestrzeni cech opisujących obiekty podlegające automatycznej klasyfikacji.

EN

In the paper a vision system is described. The purpose of the vision system is to recognise the types of integrated circuits. Such system can be used in a robot vision system in the automatic assembly line or can be used as a diagnostic system for montage operations verification. In the paper all the image processing operations necessary for integrated circuit recognition are thoroughly described. Special attention is paid to the operations such as : acquisition, image processing, image segmentation, feature extraction and classification. As a classification method a minimal - distance method is chosen which is based on the search of nearest neighbour in the feature space.