16 citations · 20 across the 6 of their papers we have counts for
6 papers
Exploiting Boundary Loss for the Hierarchical Panoptic Segmentation of Plants and Leaves
Madeleine Darbyshire, Elizabeth Sklar, Simon Parsons
Precision agriculture leverages data and machine learning so that farmers can monitor their crops and target interventions precisely. This enables the precision application of herb…
Critical-Questions-of-Thought: Steering LLM reasoning with Argumentative Querying
Federico Castagna, Isabel Sassoon, Simon Parsons
Studies have underscored how, regardless of the recent breakthrough and swift advances in AI research, even state-of-the-art Large Language models (LLMs) continue to struggle when…
Can formal argumentative reasoning enhance LLMs performances?
Federico Castagna, Isabel Sassoon, Simon Parsons
Recent years witnessed significant performance advancements in deep-learning-driven natural language models, with a strong focus on the development and release of Large Language Mo…
Multispectral Fine-Grained Classification of Blackgrass in Wheat and Barley Crops
Madeleine Darbyshire, Shaun Coutts, Eleanor Hammond +6
As the burden of herbicide resistance grows and the environmental costs of excessive herbicide use become clear, new approaches to managing weed populations are needed. This is par…
Computational Argumentation-based Chatbots: a Survey
Federico Castagna, Nadin Kokciyan, Isabel Sassoon +2
Chatbots are conversational software applications designed to interact dialectically with users for a plethora of different purposes. Surprisingly, these colloquial agents have onl…
Hierarchical Mask2Former: Panoptic Segmentation of Crops, Weeds and Leaves
Madeleine Darbyshire, Elizabeth Sklar, Simon Parsons
Advancements in machine vision that enable detailed inferences to be made from images have the potential to transform many sectors including agriculture. Precision agriculture, whe…