Compared to other anomalous video event detection approaches that analyze object trajectories
only, we propose a context-aware method to detect anomalies. By tracking all moving …

The emergence of deep learning has considerably advanced the state-of-the-art in cardiac
magnetic resonance (CMR) segmentation. Many techniques have been proposed over the …

This paper reviews state-of-the-art research solutions across the spectrum of medical imaging
informatics, discusses clinical translation, and provides future directions for advancing …

Image-based plant phenotyping is a growing application area of computer vision in agriculture.
A key task is the segmentation of all individual leaves in images. Here we focus on the …

Image-based approaches to plant phenotyping are gaining momentum providing fertile ground
for several interesting vision tasks where fine-grained categorization is necessary, such …

We propose a multi-input multi-output fully convolutional neural network model for MRI synthesis.
The model is robust to missing data, as it benefits from, but does not require, additional …

While the importance of automatic image analysis is continuously increasing, recent meta-research
revealed major flaws with respect to algorithm validation. Performance metrics are …

Plant phenotyping is the identification of effects on the phenotype (ie, the plant appearance
and performance) as a result of genotype differences (ie, differences in the genetic code) and …

This paper demonstrates the potential for synthesis of medical images in one modality (eg
MR) from images in another (eg CT) using a CycleGAN [ 24 ] architecture. The synthesis can …

Causal machine learning (CML) has experienced increasing popularity in healthcare.
Beyond the inherent capabilities of adding domain knowledge into learning systems, CML …