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On methods for improving the accuracy of multi-class classification on unbalanced data

Sevastianov L.A., Shchetinin E.Y.

, the algorithm may be retrained, which leads to incorrect estimates of object classification. Thus, in order

MGFEEN: a multi-granularity feature encoding ensemble network for remote sensing image classification

Jean Bosco Musabe, Jean Pierre Rutarindwa, Muthanna M.S., Jean Pierre Kwizera, Muthanna Ammar, Abd El-Latif A.A.

classification accuracy. In this paper, we introduce a multi-granularity feature encoding ensemble network

АУДИО- И ВИДЕОМАТЕРИАЛЫ В СТЕРЕОСКОПИЧЕСКОЙ МОДЕЛИ ПРЕПОДАВАНИЯ КИТАЙСКОГО ЯЗЫКА

Сыюань Ли

materials are widely used. Based on the classification and analysis of these materials, effective teaching

Multi-agent system for сontrol sound information

Visniakou, U. A., Вишняков, В. А., Shaya, B. H., Сайя, Б. Х.

The multi-agent system for monitoring sound information (MAMS) in the environment is a set

Hierarchical multispectral image classification based on self organized maps

Saveliev A., Dobrinin D.

of that SOM classification from the p-dimensional input image space to the 2-dimensional points on a plane

Implementation of data fusion to increase the efficiency of classification of precancerous skin states using in vivo bimodal spectroscopic technique

Kupriyanov, Valentin, Blondel, Walter, Daul, Christian, Amouroux, Marine, Kistenev, Yury V.

This study presents the results of the classification of diffuse reflectance (DR) spectra

Classification Criteria: Defining the Specific Features of Corporate Conflicts

Frolova E.E., Inshakova A.O., Dolinskaya V.V.

Having investigated the most popular corporate conflicts' classification grounds, in the chapter

Invariant manifolds of p-adic renormalization groups

Missarov M.

Invariant manifolds of p-adic renormalization groups in terms of (4-d)-expansion and dimensional

Convolutional Neural Network Based Deep Neural Network Model for Electrocardiogram Records Classification

Khudhur A.M., Alwan M.H., Al Omairi Q., Mahmood O.A., Hammadi Y.I., Muthanna M.S.A., Aziz A., Muthanna A.

database. The proposed method involves the utilization of a 16-layer deep one-dimensional convolutional

The efficiency of heuristic subject-oriented learning for students’ multi-dimensional thinking self-development

Andreyev V.

’ multi-dimensional thinking self-development. The relevance of the studied issue connected with students

Страница 3 из 2075

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