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Camera Model Identification Using Convolutional Neural Networks
Artur Kuzin, Artur Fattakhov, Ilya Kibardin +2
Source camera identification is the process of determining which camera or model has been used to capture an image. In the recent years, there has been a rapid growth of research i…
Albumentations: fast and flexible image augmentations
Alexander Buslaev, Alex Parinov, Eugene Khvedchenya +2
Data augmentation is a commonly used technique for increasing both the size and the diversity of labeled training sets by leveraging input transformations that preserve output labe…
Fully Convolutional Network for Automatic Road Extraction from Satellite Imagery
Alexander V. Buslaev, Selim S. Seferbekov, Vladimir I. Iglovikov +1
Analysis of high-resolution satellite images has been an important research topic for traffic management, city planning, and road monitoring. One of the problems here is automatic…
Feature Pyramid Network for Multi-Class Land Segmentation
Selim S. Seferbekov, Vladimir I. Iglovikov, Alexander V. Buslaev +1
Semantic segmentation is in-demand in satellite imagery processing. Because of the complex environment, automatic categorization and segmentation of land cover is a challenging pro…
TernausNetV2: Fully Convolutional Network for Instance Segmentation
Vladimir I. Iglovikov, Selim Seferbekov, Alexander V. Buslaev +1
The most common approaches to instance segmentation are complex and use two-stage networks with object proposals, conditional random-fields, template matching or recurrent neural n…
Angiodysplasia Detection and Localization Using Deep Convolutional Neural Networks
Alexey Shvets, Vladimir Iglovikov, Alexander Rakhlin +1
Accurate detection and localization for angiodysplasia lesions is an important problem in early stage diagnostics of gastrointestinal bleeding and anemia. Gold-standard for angiody…
Deep Convolutional Neural Networks for Breast Cancer Histology Image Analysis
Alexander Rakhlin, Alexey Shvets, Vladimir Iglovikov +1
Breast cancer is one of the main causes of cancer death worldwide. Early diagnostics significantly increases the chances of correct treatment and survival, but this process is tedi…
Automatic Instrument Segmentation in Robot-Assisted Surgery Using Deep Learning
Alexey Shvets, Alexander Rakhlin, Alexandr A. Kalinin +1
Semantic segmentation of robotic instruments is an important problem for the robot-assisted surgery. One of the main challenges is to correctly detect an instrument's position for…
TernausNet: U-Net with VGG11 Encoder Pre-Trained on ImageNet for Image Segmentation
Vladimir Iglovikov, Alexey Shvets
Pixel-wise image segmentation is demanding task in computer vision. Classical U-Net architectures composed of encoders and decoders are very popular for segmentation of medical ima…