activity
20182021
most citedGenerative adversarial network with object detector discriminator for enhanced defect detection on ultrasonic B-scans

63 citations · 123 across the 6 of their papers we have counts for

collaborators

9 papers

eess.IV202163 cited

Generative adversarial network with object detector discriminator for enhanced defect detection on ultrasonic B-scans

Luka Posilović, Duje Medak, Marko Subasic +2

Non-destructive testing is a set of techniques for defect detection in materials. While the set of imaging techniques are manifold, ultrasonic imaging is the one used the most. The…

cs.CV20201 cited

Illumination Estimation Challenge: experience of past two years

Egor Ershov, Alex Savchik, Ilya Semenkov +15

Illumination estimation is the essential step of computational color constancy, one of the core parts of various image processing pipelines of modern digital cameras. Having an acc…

cs.CV202027 cited

The Cube++ Illumination Estimation Dataset

Egor Ershov, Alex Savchik, Illya Semenkov +6

Computational color constancy has the important task of reducing the influence of the scene illumination on the object colors. As such, it is an essential part of the image process…

eess.IV2020

Microvasculature Segmentation and Inter-capillary Area Quantification of the Deep Vascular Complex using Transfer Learning

Julian Lo, Morgan Heisler, Vinicius Vanzan +6

Purpose: Optical Coherence Tomography Angiography (OCT-A) permits visualization of the changes to the retinal circulation due to diabetic retinopathy (DR), a microvascular complica…

eess.IV201913 cited

Deep learning vessel segmentation and quantification of the foveal avascular zone using commercial and prototype OCT-A platforms

Morgan Heisler, Forson Chan, Zaid Mammo +15

Automatic quantification of perifoveal vessel densities in optical coherence tomography angiography (OCT-A) images face challenges such as variable intra- and inter-image signal to…

astro-ph.IM201915 cited

AXS: A framework for fast astronomical data processing based on Apache Spark

Petar Zečević, Colin T. Slater, Mario Jurić +5

We introduce AXS (Astronomy eXtensions for Spark), a scalable open-source astronomical data analysis framework built on Apache Spark, a widely used industry-standard engine for big…