title: Ð Ð°Ð·ÑÐ°Ð±Ð¾ÑÐºÐ° ÑÐ¸ÑÑÐµÐ¼Ñ ÑÐ°ÑÐ¿Ð¾Ð·Ð½Ð°Ð²Ð°Ð½Ð¸Ñ Ð´ÐµÑÐµÐºÑÐ¾Ð² ÑÑÑÐ¾Ð¸ÑÐµÐ»ÑÐ½ÑÑ ÐºÐ¾Ð½ÑÑÑÑÐºÑÐ¸Ð¹ Ð¿Ð¾ ÑÐ¾ÑÐ¾Ð³ÑÐ°ÑÐ¸ÑÐ¼
title: Ð²ÑÐ¿ÑÑÐºÐ½Ð°Ñ ÐºÐ²Ð°Ð»Ð¸ÑÐ¸ÐºÐ°ÑÐ¸Ð¾Ð½Ð½Ð°Ñ ÑÐ°Ð±Ð¾ÑÐ° Ð±Ð°ÐºÐ°Ð»Ð°Ð²ÑÐ°
titleType: Subtitle
title: Development of a system forrecognizing defects in building structures from photographs
Creators: name: ÐÑÐ·Ð½ÐµÑÐ¾Ð²Ð°, ÐÐ°ÑÑÑ
Publisher: name: Ð¡Ð°Ð½ÐºÑ-ÐÐµÑÐµÑÐ±ÑÑÐ³ÑÐºÐ¸Ð¹ Ð¿Ð¾Ð»Ð¸ÑÐµÑÐ½Ð¸ÑÐµÑÐºÐ¸Ð¹ ÑÐ½Ð¸Ð²ÐµÑÑÐ¸ÑÐµÑ ÐÐµÑÑÐ° ÐÐµÐ»Ð¸ÐºÐ¾Ð³Ð¾
Year: 2023
Subjects: ÑÐ°ÑÐ¿Ð¾Ð·Ð½Ð°Ð²Ð°Ð½Ð¸Ðµ Ð´ÐµÑÐµÐºÑÐ¾Ð²
ÑÐ°ÑÐ°Ð´Ñ Ð·Ð´Ð°Ð½Ð¸Ð¹
Ð³Ð»ÑÐ±Ð¾ÐºÐ¾Ðµ Ð¾Ð±ÑÑÐµÐ½Ð¸Ðµ
Ð¼ÐµÑÐ¾Ð´Ñ Ð´ÐµÑÐµÐºÑÐ¸Ð¸ Ð¸Ð·Ð¾Ð±ÑÐ°Ð¶ÐµÐ½Ð¸Ð¹
defect detection
building facades
deep learning
image detection methods

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description: A system for automatic recognition of defects on building facades using deep learning was researched and developed. Analytical work was carried out, including a review of the subject area and existing analogues. The optimal methods for image detection, as well as the technological stack for the implementation of the system, were selected. The focus was on training the image detector based on the YOLOv5 model. A training sample was created, models were trained, and image augmentation was applied. The results of training of various models are analyzed and compared. To improve the quality of neural network predictions, a post-processing module was developed. It includes filtering predictions using various criteria and rules to eliminate errors and improve recognition accuracy. The conducted testing showed the high efficiency of the developed system in recognizing defects on the facades of buildings. The results of the study can be useful for specialists in the field of building inspection, construction, and architecture, allowing to reduce the time and resources spent on detecting defects and assessing the condition of facades.