Spitsin V.G.
University
National research Tomsk state university
Level of English language proficiency
Advanced
The field of study for which the graduate student will be
accepted
accepted
Informatics and computer engineering,
Computer and Information Sciences
Computer and Information Sciences
The code of the field of study for which the graduate student
will be accepted
will be accepted
09.06.01 02.06.01
List of research projects of a potential supervisor
(participation / leadership)
(participation / leadership)
Head of the initiative project "Creation of an intelligent system for detecting, recognizing and understanding distorted printed texts in images and videos" supported by the RFFI grant No. 18-08-00977a.
List of possible research topics
Development of methods of computational intelligence.
Application of artificial neural networks and evolutionary algorithms for image processing and analysis.
Recognition of patterns in images based on the use of a hierarchical temporary network.
Recognition of gestures on video sequences.
Face recognition in images and video sequences
Application of artificial neural networks and evolutionary algorithms for image processing and analysis.
Recognition of patterns in images based on the use of a hierarchical temporary network.
Recognition of gestures on video sequences.
Face recognition in images and video sequences
Supervisor’s
main publications
main publications
1) Канаева И.А., Иванова Ю.А., Спицын В.Г. Сегментация дефектов дорожного покрытия на основе формирования синтетических выборок с помощью глубоких генеративно-состязательных сверточных сетей // Компьютерная оптика. 2021. Т. 45, № 6. С. 907‒916. DOI: 10.18287/2412-6179-CO-844
2) Deep convolutional generative adversarial network-based synthesis of datasets for road pavement distress segmentation Kanaeva, I.A., Ivanova, Y.A., Spitsyn, V.G. Computer Optics, 2021, 45(6), P. 907–916
3) Automatic generation of short texts based on the use of neural networks lstm and SeqGAN Krivosheev, N.A., Ivanova, Y.A., Spitsyn, V.G.Vestnik Tomskogo Gosudarstvennogo Universiteta - Upravlenie, Vychislitel'naya Tekhnika i Informatika, 2021, (57), P. 118–130
4) Druki A.A., Spitsyn V.G., Arkalykov E.U. Semantic segmentation algorithms of the Earth's surface pictures based on neural network methods //Вестн. Том. гос. ун-та. УВТиИ. 2020. № 51. P. 72-78.
5) Motor imagery recognition in electroencephalograms using convolutional neural networks Bragin, A.D., Spitsyn, V.G. Computer Optics, 2020, 44(3), P. 482–487
6) Друки А.А., В.Г. Спицын В.Г., Болотова Ю.А., Олива Д., Гельгинберг А.М. Разработка алгоритма отслеживания лица человека на основе применения оптического потока // Научная визуализация, Т. 10, № 5, 2018, С. 86 – 101.
7) Druki A.A., Spitsyn V.G., BolotovaYu.A., Oliva D., Gelginberg A.V. Development of the human face tracking algorithm based on the optical flow application // Scientific Visualization, Vol. 10, №. 5, 2018, pp. 86 – 101.
8) Application of deep learning neural networks for solving the problem of forest fire segmentation on satellite images Vik, K.V., Druki, A.A., Grigoriev, D.S., Spitsyn, V.G.Vestnik Tomskogo Gosudarstvennogo Universiteta - Upravlenie, Vychislitel'naya Tekhnika i Informatika
9) Semantic segmentation algorithms of the Earth's surface pictures based on neural network methods Druki, A.A., Spitsyn, V.G., Arkalykov, E.U.Vestnik Tomskogo Gosudarstvennogo Universiteta - Upravlenie, Vychislitel'naya Tekhnika i Informatika
10) Development english pronunciation practicing system based on speech recognition Phan, N.H., Bui, T.T.T., Spitsyn, V.G.
2) Deep convolutional generative adversarial network-based synthesis of datasets for road pavement distress segmentation Kanaeva, I.A., Ivanova, Y.A., Spitsyn, V.G. Computer Optics, 2021, 45(6), P. 907–916
3) Automatic generation of short texts based on the use of neural networks lstm and SeqGAN Krivosheev, N.A., Ivanova, Y.A., Spitsyn, V.G.Vestnik Tomskogo Gosudarstvennogo Universiteta - Upravlenie, Vychislitel'naya Tekhnika i Informatika, 2021, (57), P. 118–130
4) Druki A.A., Spitsyn V.G., Arkalykov E.U. Semantic segmentation algorithms of the Earth's surface pictures based on neural network methods //Вестн. Том. гос. ун-та. УВТиИ. 2020. № 51. P. 72-78.
5) Motor imagery recognition in electroencephalograms using convolutional neural networks Bragin, A.D., Spitsyn, V.G. Computer Optics, 2020, 44(3), P. 482–487
6) Друки А.А., В.Г. Спицын В.Г., Болотова Ю.А., Олива Д., Гельгинберг А.М. Разработка алгоритма отслеживания лица человека на основе применения оптического потока // Научная визуализация, Т. 10, № 5, 2018, С. 86 – 101.
7) Druki A.A., Spitsyn V.G., BolotovaYu.A., Oliva D., Gelginberg A.V. Development of the human face tracking algorithm based on the optical flow application // Scientific Visualization, Vol. 10, №. 5, 2018, pp. 86 – 101.
8) Application of deep learning neural networks for solving the problem of forest fire segmentation on satellite images Vik, K.V., Druki, A.A., Grigoriev, D.S., Spitsyn, V.G.Vestnik Tomskogo Gosudarstvennogo Universiteta - Upravlenie, Vychislitel'naya Tekhnika i Informatika
9) Semantic segmentation algorithms of the Earth's surface pictures based on neural network methods Druki, A.A., Spitsyn, V.G., Arkalykov, E.U.Vestnik Tomskogo Gosudarstvennogo Universiteta - Upravlenie, Vychislitel'naya Tekhnika i Informatika
10) Development english pronunciation practicing system based on speech recognition Phan, N.H., Bui, T.T.T., Spitsyn, V.G.
