5 papers
Ctrl-A: Control-Driven Online Data Augmentation
Jesper B. Christensen, Ciaran Bench, Spencer A. Thomas +4
We introduce ControlAugment (Ctrl-A), an automated data augmentation algorithm for image-vision tasks, which incorporates principles from control theory for online adjustment of au…
Evaluating the trustworthiness of the Fréchet Inception Distance with stochastic embedding representations
Ciaran Bench, Vivek Desai, Carlijn Roozemond +2
Feature embeddings acquired from pretrained models are widely used in medical applications of deep learning to assess the characteristics of datasets; e.g. to determine the quality…
Quantifying the uncertainty of model-based synthetic image quality metrics
Ciaran Bench, Spencer A. Thomas
The quality of synthetically generated images (e.g. those produced by diffusion models) are often evaluated using information about image contents encoded by pretrained auxiliary m…
Style transfer as data augmentation: evaluating unpaired image-to-image translation models in mammography
Emir Ahmed, Spencer A. Thomas, Ciaran Bench
Several studies indicate that deep learning models can learn to detect breast cancer from mammograms (X-ray images of the breasts). However, challenges with overfitting and poor ge…
Trustworthy image-to-image translation: evaluating uncertainty calibration in unpaired training scenarios
Ciaran Bench, Emir Ahmed, Spencer A. Thomas
Mammographic screening is an effective method for detecting breast cancer, facilitating early diagnosis. However, the current need to manually inspect images places a heavy burden…