217 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- University of FloridaUS21 papers
- Monash UniversityAU16 papers
- Commonwealth Scientific and Industrial Research OrganisationAU14 papers
- The University of MelbourneAU13 papers
- Centre National de la Recherche ScientifiqueFR11 papers
- UNSW SydneyAU10 papers
- Commissariat à l'Énergie Atomique et aux Énergies AlternativesFR9 papers
- Max Planck Institute for AstronomyDE9 papers
- Max Planck Institute for Radio AstronomyDE9 papers
- University of CanterburyNZ9 papers
- Cardiff UniversityGB8 papers
- Space Science InstituteUS8 papers
5 papers · 1 filter
Learning-based estimation of cattle weight gain and its influencing factors
Muhammad Riaz Hasib Hossain, Rafiqul Islam, Shawn R. McGrath +2
Many cattle farmers still depend on manual methods to measure the live weight gain of cattle at set intervals, which is time consuming, labour intensive, and stressful for both the…
Meta-learning in healthcare: A survey
Alireza Rafiei, Ronald Moore, Sina Jahromi +2
As a subset of machine learning, meta-learning, or learning to learn, aims at improving the model's capabilities by employing prior knowledge and experience. A meta-learning paradi…
A Dynamic Programming Algorithm for Finding an Optimal Sequence of Informative Measurements
Peter N. Loxley, Ka-Wai Cheung
An informative measurement is the most efficient way to gain information about an unknown state. We present a first-principles derivation of a general-purpose dynamic programming a…
Deep Learning-based Cattle Activity Classification Using Joint Time-frequency Data Representation
Seyedeh Faezeh Hosseini Noorbin, Siamak Layeghy, Brano Kusy +3
Automated cattle activity classification allows herders to continuously monitor the health and well-being of livestock, resulting in increased quality and quantity of beef and dair…
A sparse code increases the speed and efficiency of neuro-dynamic programming for optimal control tasks with correlated inputs
Peter N. Loxley
Sparse codes in neuroscience have been suggested to offer certain computational advantages over other neural representations of sensory data. To explore this viewpoint, a sparse co…