24 citations · 27 across the 6 of their papers we have counts for
7 papers
Affine Fixed Points on Flat Manifold Pairs
Aaron Reite
In this paper we consider affine selfmaps of compact flat manifold pairs. We derive an explicit formula for the relative Nielsen number in terms of the ambient holonomy and the hol…
Attend Before Attention: Efficient and Scalable Video Understanding via Autoregressive Gazing
Baifeng Shi, Stephanie Fu, Long Lian +10
Multi-modal large language models (MLLMs) have advanced general-purpose video understanding but struggle with long, high-resolution videos -- they process every pixel equally in th…
Efficient In-Domain Question Answering for Resource-Constrained Environments
Isaac Chung, Phat Vo, Arman C. Kizilkale +1
Retrieval Augmented Generation (RAG) is a common method for integrating external knowledge into pretrained Large Language Models (LLMs) to enhance accuracy and relevancy in questio…
Debiased Learning for Remote Sensing Data
Chun-Hsiao Yeh, Xudong Wang, Stella X. Yu +4
Deep learning has had remarkable success at analyzing handheld imagery such as consumer photos due to the availability of large-scale human annotations (e.g., ImageNet). However, r…
Multi-Spectral Image Classification with Ultra-Lean Complex-Valued Models
Utkarsh Singhal, Stella X. Yu, Zackery Steck +2
Multi-spectral imagery is invaluable for remote sensing due to different spectral signatures exhibited by materials that often appear identical in greyscale and RGB imagery. Paired…
Conditional Generative Adversarial Networks for Data Augmentation and Adaptation in Remotely Sensed Imagery
Jonathan Howe, Kyle Pula, Aaron A. Reite
The difficulty in obtaining labeled data relevant to a given task is among the most common and well-known practical obstacles to applying deep learning techniques to new or even sl…
Unsupervised Feature Learning in Remote Sensing
Aaron Reite, Scott Kangas, Zackery Steck +3
The need for labeled data is among the most common and well-known practical obstacles to deploying deep learning algorithms to solve real-world problems. The current generation of…