15 citations · 16 across the 2 of their papers we have counts for
4 papers
Grassmann Iterative Linear Discriminant Analysis with Proxy Matrix Optimization
Navya Nagananda, Breton Minnehan, Andreas Savakis
Linear Discriminant Analysis (LDA) is commonly used for dimensionality reduction in pattern recognition and statistics. It is a supervised method that aims to find the most discrim…
Benchmarking Deep Trackers on Aerial Videos
Abu Md Niamul Taufique, Breton Minnehan, Andreas Savakis
In recent years, deep learning-based visual object trackers have achieved state-of-the-art performance on several visual object tracking benchmarks. However, most tracking benchmar…
Cascaded Projection: End-to-End Network Compression and Acceleration
Breton Minnehan, Andreas Savakis
We propose a data-driven approach for deep convolutional neural network compression that achieves high accuracy with high throughput and low memory requirements. Current network co…
DEFRAG: Deep Euclidean Feature Representations through Adaptation on the Grassmann Manifold
Breton Minnehan, Andreas Savakis
We propose a novel technique for training deep networks with the objective of obtaining feature representations that exist in a Euclidean space and exhibit strong clustering behavi…