13 citations · 16 across the 5 of their papers we have counts for
5 papers
Discrete Gaussian Process Representations for Optimising UAV-based Precision Weed Mapping
Jacob Swindell, Madeleine Darbyshire, Marija Popovic +1
Accurate agricultural weed mapping using UAVs is crucial for precision farming applications. Traditional methods rely on orthomosaic stitching from rigid flight paths, which is com…
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…
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…
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…
Towards practical object detection for weed spraying in precision agriculture
Adrian Salazar-Gomez, Madeleine Darbyshire, Junfeng Gao +2
The evolution of smaller, faster processors and cheaper digital storage mechanisms across the last 4-5 decades has vastly increased the opportunity to integrate intelligent technol…