Crack detection in paintings using convolutional neural networks

R Sizyakin, B Cornelis, L Meeus, H Dubois… - Ieee …, 2020 - ieeexplore.ieee.org
The accurate detection of cracks in paintings, which generally portray rich and varying
content, is a challenging task. Traditional crack detection methods are often lacking on …

Virtual restoration of paintings based on deep learning

R Sizyakin, V Voronin… - … Conference on Machine …, 2022 - spiedigitallibrary.org
Over time, crack pattern (craquelure) inevitably develops in paintings as a sign of their
ageing, sometimes accompanied by larger losses of paint (lacunas). In restoration …

Real-time Tool Defect Detection Systems

V Velmurugan, B Elamvazhudi… - … and Systems for …, 2024 - ieeexplore.ieee.org
To support the competition and to produce industrial economically, it seems mostly that
manufacturing systems must exhibit a high level of disgruntlement in their operation. Hence …

Detection of deleted frames on videos using a 3D convolutional neural network

V Voronin, R Sizyakin, A Zelensky… - Counterterrorism …, 2018 - spiedigitallibrary.org
Digital video forgery or manipulation is a modification of the digital video for fabrication,
which includes frame sequence manipulations such as deleting, insertion and swapping. In …

[PDF][PDF] A deep learning-based approach for defect detection and removing on archival photos

R Sizyakin, V Voronin, N Gapon, A Zelensky… - Electronic …, 2020 - library.imaging.org
Many archival photos are unique, existed only in a single copy. Some of them are damaged
due to improper archiving (eg affected by direct sunlight, humidity, insects, etc.) or have …

A two-stream neural network architecture for the detection and analysis of cracks in panel paintings

R Sizyakin, B Cornelis, L Meeus… - Optics, Photonics …, 2020 - spiedigitallibrary.org
Museums all over the world store a large variety of digitized paintings and other works of art
with significant historical value. Over time, these works of art deteriorate, making them lose …

Virtual restoration of paintings using adaptive adversarial neural network

R Sizyakin, V Voronin, A Zelensky… - Journal of Electronic …, 2022 - spiedigitallibrary.org
Cracks (craquelure) and paint losses are the main types of deterioration of master paintings
as they are ageing. We explore the potential of deep-learning-based methods for virtual …

Bankruptcy: What is left for the creditors? A Belgian exploratory study

JR Baeck - International Insolvency Review, 2019 - Wiley Online Library
It is sometimes alleged that in cases of bankruptcy, there is often not much left for the
creditors, especially for the ordinary unsecured creditors. This article examines, in an …

Image defect detection algorithm based on deep learning

RA Sizyakin, VV Voronin, NV Gapon… - IOP Conference …, 2019 - iopscience.iop.org
In this paper proposed a system for automatic defects detection in images. The solution to
this problem is widely used in practice. Automatic detection is found in the challenge of …

Реконструкция архивных фотографий на основе глубокого обучения

РА Сизякин, ВВ Воронин, НВ Гапон… - … систем" ДТС-2019", 2019 - elibrary.ru
В данной работе предложена система автоматического обнаружения и устранения
дефектов изображений. Автоматическое обнаружение дефектов выполняется с …