2 citations · 2 across the 4 of their papers we have counts for
5 papers
Training Over a Distribution of Hyperparameters for Enhanced Performance and Adaptability on Imbalanced Classification
Kelsey Lieberman, Swarna Kamlam Ravindran, Shuai Yuan +1
Although binary classification is a well-studied problem, training reliable classifiers under severe class imbalance remains a challenge. Recent techniques mitigate the ill effects…
Optimizing for ROC Curves on Class-Imbalanced Data by Training over a Family of Loss Functions
Kelsey Lieberman, Shuai Yuan, Swarna Kamlam Ravindran +1
Although binary classification is a well-studied problem in computer vision, training reliable classifiers under severe class imbalance remains a challenging problem. Recent work h…
RandMSAugment: A Mixed-Sample Augmentation for Limited-Data Scenarios
Swarna Kamlam Ravindran, Carlo Tomasi
The high costs of annotating large datasets suggests a need for effectively training CNNs with limited data, and data augmentation is a promising direction. We study foundational a…
CoMaL Tracking: Tracking Points at the Object Boundaries
Santhosh K. Ramakrishnan, Swarna Kamlam Ravindran, Anurag Mittal
Traditional point tracking algorithms such as the KLT use local 2D information aggregation for feature detection and tracking, due to which their performance degrades at the object…
CoMIC: Good features for detection and matching at object boundaries
Swarna Kamlam Ravindran, Anurag Mittal
Feature or interest points typically use information aggregation in 2D patches which does not remain stable at object boundaries when there is object motion against a significantly…