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Введение в обработку изображений на языке Python

учебное пособие

Введение в обработку изображений на языке Python

Abstract

Учебное пособие является дополнительной литературой по дисциплине «Цифровая обработка многомерных сигналов» и предназначено для освоения лекционного материала, практических занятий, выполнения расчетных заданий с использованием эффективного инструмента обработки изображений на языке Python. Предназначено для студентов высших учебных заведений, обучающихся по направлениям подготовки магистров «Программная инженерия» и «Информатика и вычислительная техника». Оно может быть также использовано в системах повышения квалификации, в учреждениях дополнительного профессионального образования.

The training manual is additional literature on the course "Digital processing of multidimensional signals" and is intended for mastering the lecture material, practical exercises, performing calculation tasks using an effective image processing tool in the Python language. It is intended for students of higher education institutions, studying in the master's degree programs "Software Engineering" and "Computer Science and Computer Engineering". It can also be useful in advanced training systems, in institutions of supplementary vocational education.

Keywords

Питон (Python), Изображения

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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