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cs.CV2026

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…

cs.CV2026

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…

cs.CV2024

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…

cs.CV2024

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…

cs.CV2024

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…