579 citations · 1.4k across the 9 of their papers we have counts for
12 papers
PALS: Percentile-Aware Layerwise Sparsity for LLM Pruning
Yazdan Jamshidi, Alexey Shvets
One-shot pruning methods like Wanda and SparseGPT apply the same sparsity ratio to every layer of a transformer, ignoring known variation in layer importance. We propose PALS (Perc…
Breast Tumor Cellularity Assessment using Deep Neural Networks
Alexander Rakhlin, Aleksei Tiulpin, Alexey A. Shvets +3
Breast cancer is one of the main causes of death worldwide. Histopathological cellularity assessment of residual tumors in post-surgical tissues is used to analyze a tumor's respon…
2017 Robotic Instrument Segmentation Challenge
Max Allan, Alex Shvets, Thomas Kurmann +16
In mainstream computer vision and machine learning, public datasets such as ImageNet, COCO and KITTI have helped drive enormous improvements by enabling researchers to understand t…
Deep Learning Approaches for Understanding Simple Speech Commands
Roman A. Solovyev, Maxim Vakhrushev, Alexander Radionov +2
Automatic classification of sound commands is becoming increasingly important, especially for mobile and embedded devices. Many of these devices contain both cameras and microphone…
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…
Pediatric Bone Age Assessment Using Deep Convolutional Neural Networks
Vladimir Iglovikov, Alexander Rakhlin, Alexandr Kalinin +1
Skeletal bone age assessment is a common clinical practice to diagnose endocrine and metabolic disorders in child development. In this paper, we describe a fully automated deep lea…