Serwis Infona wykorzystuje pliki cookies (ciasteczka). Są to wartości tekstowe, zapamiętywane przez przeglądarkę na urządzeniu użytkownika. Nasz serwis ma dostęp do tych wartości oraz wykorzystuje je do zapamiętania danych dotyczących użytkownika, takich jak np. ustawienia (typu widok ekranu, wybór języka interfejsu), zapamiętanie zalogowania. Korzystanie z serwisu Infona oznacza zgodę na zapis informacji i ich wykorzystanie dla celów korzytania z serwisu. Więcej informacji można znaleźć w Polityce prywatności oraz Regulaminie serwisu. Zamknięcie tego okienka potwierdza zapoznanie się z informacją o plikach cookies, akceptację polityki prywatności i regulaminu oraz sposobu wykorzystywania plików cookies w serwisie. Możesz zmienić ustawienia obsługi cookies w swojej przeglądarce.
We present a hierarchical principle for object recognition and its application to automatically classify developmental stages of C. elegans animals from a population of mixed stages. The object recognition machine consists of four hierarchical layers, each composed of units upon which evaluation functions output a label score, followed by a grouping mechanism that resolves ambiguities in the score...
So far, feather and down category recognition is often done by man with a microscope, but this method has some disadvantages. So a feather and down category recognition system is proposed in the paper, and then feather and down category recognition can be done by computer automatically. After the image processing and segmentation using GA, the triangle node of two-value image of feather and down is...
Currently, feather and down category recognition is often done by man with a microscope, but this method has some disadvantages. So a feather and down category recognition system is proposed in this paper, and feather and down category recognition is done by computer automatically. After the image processing and segmentation using GA, the triangle node of two-value image of feather is to be recognized...
This paper proposes an interactive approach for region-based image clustering and retrieval. By performing clustering before image retrieval, the search space can be reduced to those clusters that are close to the query target. First, the image is segmented to regions by using an unsupervised segmentation method. This is an area where a vast number of regions are involved. To reduce search space for...
In this paper, four individual approaches to region classification for knowledge-assisted semantic image analysis are presented and comparatively evaluated. All of the examined approaches realize knowledge-assisted analysis via implicit knowledge acquisition, i.e. are based on machine learning techniques such as support vector machines (SVMs), self organizing maps (SOMs), genetic algorithm (GA)and...
Content-based image retrieval has become an important part of information retrieval technology. Images can be viewed as high dimensional data and are usually represented by their low-level features. How to effectively find the semantic meanings of images is a central challenge in the area. In this paper, we propose an interactive platform for region-based image clustering and retrieval. A genetic...
Podaj zakres dat dla filtrowania wyświetlonych wyników. Możesz podać datę początkową, końcową lub obie daty. Daty możesz wpisać ręcznie lub wybrać za pomocą kalendarza.