Аналитический обзор\ архитектур, моделей, методов и алгоритмов\ для локализации и трекинга неригидных объектов

Аналитический обзор\ архитектур, моделей, методов и алгоритмов\ для локализации и трекинга неригидных объектов

Автор: Гриценко Г.Г., Фраленко В.П.

Журнал: Программные системы: теория и приложения @programmnye-sistemy

Рубрика: Искусственный интеллект и машинное обучение

Статья в выпуске: 4 (63) т.15, 2024 года.

Бесплатный доступ

Компьютерное зрение требует анализа видеопотока, включающего извлечение информации из кадров, обнаружение определенных объектов и сбор данных о них. После обнаружения часто требуется выполнять трекинг или слежение за объектами в видеопотоке. Неригидность или изменчивость формы препятствует анализу объектов, усложняет их обнаружение и трекинг и ухудшает локализацию. В обзоре рассмотрены архитектуры, модели, методы и алгоритмы, применяемые на практике при обнаружении и отслеживании неригидных объектов, и выделены перспективные решения.

Неригидный объект, искусственная нейронная сеть, глубокое обучение, локализация объектов, трекинг объектов, обнаружение пожаров и задымлений, анализ медицинских изображений

Короткий адрес: https://sciup.org/143183787

IDR: 143183787   |   DOI: 10.25209/2079-3316-2024-15-4-111-151

Список литературы Аналитический обзор\ архитектур, моделей, методов и алгоритмов\ для локализации и трекинга неригидных объектов

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