6 papers
FMG-Det: Foundation Model Guided Robust Object Detection
Darryl Hannan, Timothy Doster, Henry Kvinge +2
Collecting high quality data for object detection tasks is challenging due to the inherent subjectivity in labeling the boundaries of an object. This makes it difficult to not only…
Foundation Models for Remote Sensing: An Analysis of MLLMs for Object Localization
Darryl Hannan, John Cooper, Dylan White +3
Multimodal large language models (MLLMs) have altered the landscape of computer vision, obtaining impressive results across a wide range of tasks, especially in zero-shot settings.…
Event-to-Video Conversion for Overhead Object Detection
Darryl Hannan, Ragib Arnab, Gavin Parpart +3
Collecting overhead imagery using an event camera is desirable due to the energy efficiency of the image sensor compared to standard cameras. However, event cameras complicate down…
Implementing and Benchmarking the Locally Competitive Algorithm on the Loihi 2 Neuromorphic Processor
Gavin Parpart, Sumedh R. Risbud, Garrett T. Kenyon +1
Neuromorphic processors have garnered considerable interest in recent years for their potential in energy-efficient and high-speed computing. The Locally Competitive Algorithm (LCA…
ColMix -- A Simple Data Augmentation Framework to Improve Object Detector Performance and Robustness in Aerial Images
Cuong Ly, Grayson Jorgenson, Dan Rosa de Jesus +3
In the last decade, Convolutional Neural Network (CNN) and transformer based object detectors have achieved high performance on a large variety of datasets. Though the majority of…
Universal Fourier Attack for Time Series
Elizabeth Coda, Brad Clymer, Chance DeSmet +2
A wide variety of adversarial attacks have been proposed and explored using image and audio data. These attacks are notoriously easy to generate digitally when the attacker can dir…