Формування навчального набору для задачі обробки зображень
DOI:
https://doi.org/10.18372/1990-5548.65.14978Ключові слова:
Навчання за допомогою трансферу, навчальний набір, згорткові нейронні мережі, ансамблева топологія, обробка зображеньАнотація
Розглянуто проблему формування навчального набору для задачі обробки зображень. Показано, що ця задача має велике значення при побудові інтелектуальних медичних діагностичних систем, в яких згорткові нейронні мережі використовуються для обробки зображень (результати УЗД, КТ та МРТ). Через відсутність елементів навчальної вибірки пропонується, з одного боку, використовувати підходи штучного множення даних на основі початкової навчальної вибірки фіксованого обсягу, а з іншого боку, використовувати методи, що зменшують потреба у великих навчальних зразках як за допомогою використання ансамблевої топології (гібридні нейронні мережі), так і шляхом застосування підходу до трансферного навчання. Розроблений алгоритм формування навчального набору для завдань обробки зображень, заснований на модифікації вихідної вхідної інформації з розрахунком міри достовірності отриманої вибірки. Умови індексу – навчання за допомогою трансферу навчальний набір; згортка нейронних мереж; ансамблева топологія; обробка зображень.
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