8 citations · 15 across the 7 of their papers we have counts for
7 papers
A hemodynamic decomposition model for detecting cognitive load using functional near-infrared spectroscopy
Marco A. Pinto-Orellana, Diego C. Nascimento, Peyman Mirtaheri +3
In the current paper, we introduce a parametric data-driven model for functional near-infrared spectroscopy that decomposes a signal into a series of independent, rescaled, time-sh…
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…
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…
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…
Statistical models for short and long term forecasts of snow depth
Hugo Lewi Hammer
Forecasting of future snow depths is useful for many applications like road safety, winter sport activities, avalanche risk assessment and hydrology. Motivated by the lack of stati…
Quantile Tracking in Dynamically Varying Data Streams Using a Generalized Exponentially Weighted Average of Observations
Hugo Lewi Hammer, Anis Yazidi, Håvard Rue
The Exponentially Weighted Average (EWA) of observations is known to be state-of-art estimator for tracking expectations of dynamically varying data stream distributions. However,…