2 citations · 3 across the 5 of their papers we have counts for
5 papers
DAVIS-Ag: A Synthetic Plant Dataset for Prototyping Domain-Inspired Active Vision in Agricultural Robots
Taeyeong Choi, Dario Guevara, Zifei Cheng +5
In agricultural environments, viewpoint planning can be a critical functionality for a robot with visual sensors to obtain informative observations of objects of interest (e.g., fr…
Self-supervised Representation Learning for Reliable Robotic Monitoring of Fruit Anomalies
Taeyeong Choi, Owen Would, Adrian Salazar-Gomez +1
Data augmentation can be a simple yet powerful tool for autonomous robots to fully utilise available data for selfsupervised identification of atypical scenes or objects. State-of-…
Beyond Tracking: Using Deep Learning to Discover Novel Interactions in Biological Swarms
Taeyeong Choi, Benjamin Pyenson, Juergen Liebig +1
Most deep-learning frameworks for understanding biological swarms are designed to fit perceptive models of group behavior to individual-level data (e.g., spatial coordinates of ide…
Adaptive Selection of Informative Path Planning Strategies via Reinforcement Learning
Taeyeong Choi, Grzegorz Cielniak
In our previous work, we designed a systematic policy to prioritize sampling locations to lead significant accuracy improvement in spatial interpolation by using the prediction unc…
Identification of Abnormal States in Videos of Ants Undergoing Social Phase Change
Taeyeong Choi, Benjamin Pyenson, Juergen Liebig +1
Biology is both an important application area and a source of motivation for development of advanced machine learning techniques. Although much attention has been paid to large and…