activity
20172023
most citedMetrics reloaded: Recommendations for image analysis validation

469 citations · 1.5k across the 48 of their papers we have counts for

collaborators
Showing 2019Show all

7 papers · 1 filter

eess.IV2019

Kvasir-SEG: A Segmented Polyp Dataset

Debesh Jha, Pia H. Smedsrud, Michael A. Riegler +4

Pixel-wise image segmentation is a highly demanding task in medical-image analysis. In practice, it is difficult to find annotated medical images with corresponding segmentation ma…

eess.IV2019

ResUNet++: An Advanced Architecture for Medical Image Segmentation

Debesh Jha, Pia H. Smedsrud, Michael A. Riegler +4

Accurate computer-aided polyp detection and segmentation during colonoscopy examinations can help endoscopists resect abnormal tissue and thereby decrease chances of polyps growing…

cs.CV2019★ 8 cited

Extracting temporal features into a spatial domain using autoencoders for sperm video analysis

Vajira Thambawita, Pål Halvorsen, Hugo Hammer +2

In this paper, we present a two-step deep learning method that is used to predict sperm motility and morphology-based on video recordings of human spermatozoa. First, we use an aut…

eess.IV2019★ 4 cited

Stacked dense optical flows and dropout layers to predict sperm motility and morphology

Vajira Thambawita, Pål Halvorsen, Hugo Hammer +2

In this paper, we analyse two deep learning methods to predict sperm motility and sperm morphology from sperm videos. We use two different inputs: stacked pure frames of videos and…

cs.LG2019

Machine Learning-Based Analysis of Sperm Videos and Participant Data for Male Fertility Prediction

Steven A. Hicks, Jorunn M. Andersen, Oliwia Witczak +5

Methods for automatic analysis of clinical data are usually targeted towards a specific modality and do not make use of all relevant data available. In the field of male human repr…

cs.CV2019★ 4 cited

Multi-Modal Machine Learning for Flood Detection in News, Social Media and Satellite Sequences

Kashif Ahmad, Konstantin Pogorelov, Mohib Ullah +4

In this paper we present our methods for the MediaEval 2019 Mul-timedia Satellite Task, which is aiming to extract complementaryinformation associated with adverse events from Soci…

cs.IR2019

Automatic detection of passable roads after floods in remote sensed and social media data

Kashif Ahmad, Konstantin Pogorelov, Michael Riegler +4

This paper addresses the problem of floods classification and floods aftermath detection utilizing both social media and satellite imagery. Automatic detection of disasters such as…