7 citations · 17 across the 8 of their papers we have counts for
8 papers
Data Leakage Inflates Generalizability of Power Outage Prediction Models
Yamil Essus, Ranga Raju Vatsavai, Benjamin Rachunok
Power outage prediction models are increasingly used in assessments of climate-driven infrastructure risk, yet current evaluation practices obscure whether these models generalize…
Fidelity-Diversity-Consistency (FDC): Data Pruning for Remote Sensing Change Detection
Dongyao Zhu, Ranga Raju Vatsavai
Despite the success of data pruning (DP) in reducing training data sizes and improving downstream model performance in classification and segmentation tasks, its potential in remot…
Consistency Regularization with Generative Adversarial Networks for Semi-Supervised Learning
Zexi Chen, Bharathkumar Ramachandra, Ranga Raju Vatsavai
Generative Adversarial Networks (GANs) based semi-supervised learning (SSL) approaches are shown to improve classification performance by utilizing a large number of unlabeled samp…
Local Clustering with Mean Teacher for Semi-supervised Learning
Zexi Chen, Benjamin Dutton, Bharathkumar Ramachandra +2
The Mean Teacher (MT) model of Tarvainen and Valpola has shown favorable performance on several semi-supervised benchmark datasets. MT maintains a teacher model's weights as the ex…
A Survey of Single-Scene Video Anomaly Detection
Bharathkumar Ramachandra, Michael J. Jones, Ranga Raju Vatsavai
This survey article summarizes research trends on the topic of anomaly detection in video feeds of a single scene. We discuss the various problem formulations, publicly available d…
Learning a distance function with a Siamese network to localize anomalies in videos
Bharathkumar Ramachandra, Michael J. Jones, Ranga Raju Vatsavai
This work introduces a new approach to localize anomalies in surveillance video. The main novelty is the idea of using a Siamese convolutional neural network (CNN) to learn a dista…
Estimating a Manifold from a Tangent Bundle Learner
Bharathkumar Ramachandra, Benjamin Dutton, Ranga Raju Vatsavai
Manifold hypotheses are typically used for tasks such as dimensionality reduction, interpolation, or improving classification performance. In the less common problem of manifold es…
Relational Long Short-Term Memory for Video Action Recognition
Zexi Chen, Bharathkumar Ramachandra, Tianfu Wu +1
Spatial and temporal relationships, both short-range and long-range, between objects in videos, are key cues for recognizing actions. It is a challenging problem to model them join…