Search Results for author:
Found 8 papers, 2 papers with code
Enhancing Fairness of Visual Attribute Predictors
The performance of deep neural networks for image recognition tasks such as predicting a smiling face is known to degrade with under-represented classes of sensitive attributes.
Fairness by Learning Orthogonal Disentangled Representations
We explicitly enforce the meaningful representation to be agnostic to sensitive information by entropy maximization.
Deep Attention Based Semi-Supervised 2D-Pose Estimation for Surgical Instruments
To this end, a lightweight network architecture is introduced and mean teacher, virtual adversarial training and pseudo-labeling algorithms are evaluated on 2D-pose estimation for surgical instruments.
Multi-scale Microaneurysms Segmentation Using Embedding Triplet Loss
To enhance the discriminative power of the classification model, we incorporate triplet embedding loss with a selective sampling routine.
Learning Interpretable Disentangled Representations using Adversarial VAEs
Learning Interpretable representation in medical applications is becoming essential for adopting data-driven models into clinical practice.
Towards Robotic Eye Surgery: Marker-free, Online Hand-eye Calibration using Optical Coherence Tomography Images
Ophthalmic microsurgery is known to be a challenging operation, which requires very precise and dexterous manipulation.
Fast 5DOF Needle Tracking in iOCT
We propose to build on its desirable qualities and present a method for tracking the orientation and location of a surgical needle.
Concurrent Segmentation and Localization for Tracking of Surgical Instruments
Real-time instrument tracking is a crucial requirement for various computer-assisted interventions.
