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[Submitted on 29 May 2024] View a PDF of the paper titled Safety through Permissibility: Shield Construction for Fast and Safe Reinforcement Learning, by Alexander Politowicz and 2 other authors View PDF HTML (experimental) Abstract:Designing Reinforcement Learning (RL) solutions for real-life problems remains a significant challenge. A major area of concern is safety. "Shielding" is a popular technique to enforce safety in RL by turning user-defined safety specifications into safe agent behavior. However, these methods either suffer from extreme learning delays, demand extensive human effort in designing models and safe domains in the problem, or require pre-computation. In this paper,…

arXiv:2405.19413v1 Announce Type: new Abstract: Thermal cameras are an important tool for agricultural research because they allow for non-invasive measurement of plant temperature, which relates to important photochemical, hydraulic, and agronomic traits. Utilizing low-cost thermal cameras can lower the barrier to introducing thermal imaging in agricultural research and production. This paper presents an approach to improve the temperature accuracy and image quality of low-cost thermal imaging cameras for agricultural applications. Leveraging advancements in computer vision techniques, particularly deep learning networks, we propose a method, called $textbf{VisTA-SR}$ ($textbf{Vis}$ual & $textbf{T}$hermal $textbf{A}$lignment and $textbf{S}$uper-$textbf{R}$esolution Enhancement) that combines RGB and thermal images to…

arXiv:2405.19426v1 Announce Type: new Abstract: Reading fluency assessment is a critical component of literacy programmes, serving to guide and monitor early education interventions. Given the resource intensive nature of the exercise when conducted by teachers, the development of automatic tools that can operate on audio recordings of oral reading is attractive as an objective and highly scalable solution. Multiple complex aspects such as accuracy, rate and expressiveness underlie human judgements of reading fluency. In this work, we investigate end-to-end modeling on a training dataset of children's audio recordings of story texts labeled by human experts. The pre-trained wav2vec2.0 model is…