1 citations · 1 across the 13 of their papers we have counts for
13 papers
ReconVLA: An Uncertainty-Guided and Failure-Aware Vision-Language-Action Framework for Robotic Control
Lingling Chen, Zongyao Lyu, William J. Beksi
Vision-language-action (VLA) models have emerged as generalist robotic controllers capable of mapping visual observations and natural language instructions to continuous action seq…
UEOF: A Benchmark Dataset for Underwater Event-Based Optical Flow
Nick Truong, Pritam P. Karmokar, William J. Beksi
Underwater imaging is fundamentally challenging due to wavelength-dependent light attenuation, strong scattering from suspended particles, turbidity-induced blur, and non-uniform i…
Movement Primitives in Robotics: A Comprehensive Survey
Nolan B. Gutierrez, Joseph M. Cloud, William J. Beksi
Biological systems exhibit a continuous stream of movements, consisting of sequential segments, that allow them to perform complex tasks in a creative and versatile fashion. This o…
Inertia-Informed Orientation Priors for Event-Based Optical Flow Estimation
Pritam P. Karmokar, William J. Beksi
Event cameras, by virtue of their working principle, directly encode motion within a scene. Many learning-based and model-based methods exist that estimate event-based optical flow…
Secrets of Edge-Informed Contrast Maximization for Event-Based Vision
Pritam P. Karmokar, Quan H. Nguyen, William J. Beksi
Event cameras capture the motion of intensity gradients (edges) in the image plane in the form of rapid asynchronous events. When accumulated in 2D histograms, these events depict…
Semi-Supervised Variational Adversarial Active Learning via Learning to Rank and Agreement-Based Pseudo Labeling
Zongyao Lyu, William J. Beksi
Active learning aims to alleviate the amount of labor involved in data labeling by automating the selection of unlabeled samples via an acquisition function. For example, variation…
Few-Shot Fruit Segmentation via Transfer Learning
Jordan A. James, Heather K. Manching, Amanda M. Hulse-Kemp +1
Advancements in machine learning, computer vision, and robotics have paved the way for transformative solutions in various domains, particularly in agriculture. For example, accura…
A Human-Centered Approach for Bootstrapping Causal Graph Creation
Minh Q. Tram, Nolan B. Gutierrez, William J. Beksi
Causal inference, a cornerstone in disciplines such as economics, genomics, and medicine, is increasingly being recognized as fundamental to advancing the field of robotics. In par…
CitDet: A Benchmark Dataset for Citrus Fruit Detection
Jordan A. James, Heather K. Manching, Matthew R. Mattia +3
In this letter, we present a new dataset to advance the state of the art in detecting citrus fruit and accurately estimate yield on trees affected by the Huanglongbing (HLB) diseas…
Intuitive Robot Integration via Virtual Reality Workspaces
Minh Q. Tram, Joseph M. Cloud, William J. Beksi
As robots become increasingly prominent in diverse industrial settings, the desire for an accessible and reliable system has correspondingly increased. Yet, the task of meaningfull…
MetaMax: Improved Open-Set Deep Neural Networks via Weibull Calibration
Zongyao Lyu, Nolan B. Gutierrez, William J. Beksi
Open-set recognition refers to the problem in which classes that were not seen during training appear at inference time. This requires the ability to identify instances of novel cl…
Evaluating Uncertainty Calibration for Open-Set Recognition
Zongyao Lyu, Nolan B. Gutierrez, William J. Beksi
Despite achieving enormous success in predictive accuracy for visual classification problems, deep neural networks (DNNs) suffer from providing overconfident probabilities on out-o…
Thermal Image Super-Resolution Using Second-Order Channel Attention with Varying Receptive Fields
Nolan B. Gutierrez, William J. Beksi
Thermal images model the long-infrared range of the electromagnetic spectrum and provide meaningful information even when there is no visible illumination. Yet, unlike imagery that…