Kulyabov D.S. - list of publications

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DEEP NEURAL NETWORKS FOR EMOTION RECOGNITION

Article

Shchetinin E.Y., Sevastianov L.A., Kulyabov D.S., Ayrjan E.A., Demidova A.V.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 12563 LNCS. 2020. P. 365-379

SKIN CANCER CLASSIFICATION COMPUTER SYSTEM DEVELOPMENT WITH DEEP LEARNING

Article

Demidova A.V., Kulyabov D.S., Shchetinin E.Yu.

CEUR Workshop Proceedings. CEUR-WS. Vol. 2639. 2020. P. 57-69

ON IMPROVING THE ACCURACY OF THE CLASSIFICATION ON IMBALANCED CLASSES WITH MACHINE LEARNING

Article

Shchetinin E.Y., Sevastianov L.A., Kulyabov D.S., Ayrjan E.A.

Distributed computer and communication networks: control, computation, communications (DCCN-2020). Институт проблем управления им. В.А. Трапезникова РАН. 2020. P. 130-138

AN EFFECTIVE STABLE NUMERICAL METHOD FOR INTEGRATING HIGHLY OSCILLATING FUNCTIONS WITH A LINEAR PHASE

Article

Sevastianov L.A., Lovetskiy K.P., Kulyabov D.S.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 12138 LNCS. 2020. P. 29-43

MELANOMA DETECTION COMPUTER SYSTEM DEVELOPMENT WITH DEEP NEURAL NETWORKS

Article

Shchetinin E.Y., Sevastianov L.A., Kulyabov D.S., Ayryan E.A., Demidova A.V.

Communications in Computer and Information Science. Springer Verlag. Vol. 1337. 2020. P. 422-434

КЛАССИФИКАЦИЯ ПОВРЕЖДЕНИЙ КОЖИ ПО ДАННЫМ ДЕРМАСКОПИИ С ИСПОЛЬЗОВАНИЕМ МЕТОДОВ ГЛУБОКОГО ОБУЧЕНИЯ

Article

Щетинин Е.Ю., Севастьянов Л.А., Демидова А.В., Кулябов Д.С.

Математическая биология и биоинформатика. Институт прикладной математики им. М.В. Келдыша РАН. Vol. 15. 2020. P. 180-194

COMPARATIVE ANALYSIS OF MACHINE LEARNING METHODS BY THE EXAMPLE OF THE PROBLEM OF DETERMINING MUON DECAY

Article

Gevorkyan M.N., Demidova A.V., Kulyabov D.S.

Discrete and Continuous Models and Applied Computational Science. Федеральное государственное автономное образовательное учреждение высшего образования Российский университет дружбы народов (РУДН). Vol. 28. 2020. P. 105-119

DIAGRAM REPRESENTATION FOR THE CLOSED AND OPEN SCHLOGL MODEL

Article

Апреутесей А.М., Федоров А.В., Королькова А.В., Кулябов Д.С.

Системы управления, сложные системы: моделирование, устойчивость, стабилизация, интеллектуальные технологии. Елецкий государственный университет им. И.А. Бунина. 2020. P. 156-162

HYBRID MODELLING OF THE RED ALGORITHM IN THE JULIA LANGUAGE

Article

Apreutesey A.M.Y., Korolkova A.V., Kulyabov D.S.

Journal of Physics: Conference Series. Institute of Physics Publishing. Vol. 1694. 2020.

THE MULTI-MODEL APPROACH TO THE STUDY OF COMPLEX SYSTEMS USING THE EXAMPLE OF THE RED ACTIVE QUEUE MANAGEMENT ALGORITHM

Article

Korolkova A.V., Kulyabov D.S., Hnatiˇc Michal

Distributed computer and communication networks: control, computation, communications (DCCN-2020). Институт проблем управления им. В.А. Трапезникова РАН. 2020. P. 418-425

PRACTICAL APPLICATION OF THE MULTI-MODEL APPROACH IN THE STUDY OF COMPLEX SYSTEMS

Article

Korolkova A.V., Kulyabov D.S., Hnatič M.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 12563 LNCS. 2020. P. 526-537

PARALINGUISTIC MODEL FOR EMOTIONS RECOGNITION WITH DEEP NEURAL NETWORKS

Article

Shchetinin E.Y., Sevastianov L.A., Kulyabov D.S., Ayrjan E.A., Demidova A.V.

Distributed computer and communication networks: control, computation, communications (DCCN-2020). Институт проблем управления им. В.А. Трапезникова РАН. 2020. P. 42-50