266 citations · 416 across the 10 of their papers we have counts for
6 papers · 1 filter
Virtual Temporal Samples for Recurrent Neural Networks: applied to semantic segmentation in agriculture
Alireza Ahmadi, Michael Halstead, Chris McCool
This paper explores the potential for performing temporal semantic segmentation in the context of agricultural robotics without temporally labelled data. We achieve this by proposi…
Fruit Quantity and Quality Estimation using a Robotic Vision System
M. Halstead, C. McCool, S. Denman +2
Accurate localisation of crop remains highly challenging in unstructured environments such as farms. Many of the developed systems still rely on the use of hand selected features f…
Towards Unsupervised Weed Scouting for Agricultural Robotics
David Hall, Feras Dayoub, Jason Kulk +1
Weed scouting is an important part of modern integrated weed management but can be time consuming and sparse when performed manually. Automated weed scouting and weed destruction h…
Subset Feature Learning for Fine-Grained Category Classification
Zongyuan Ge, Christopher Mccool, Conrad Sanderson +1
Fine-grained categorisation has been a challenging problem due to small inter-class variation, large intra-class variation and low number of training images. We propose a learning…
Modelling Local Deep Convolutional Neural Network Features to Improve Fine-Grained Image Classification
ZongYuan Ge, Chris McCool, Conrad Sanderson +1
We propose a local modelling approach using deep convolutional neural networks (CNNs) for fine-grained image classification. Recently, deep CNNs trained from large datasets have co…
Multi-Action Recognition via Stochastic Modelling of Optical Flow and Gradients
Johanna Carvajal, Conrad Sanderson, Chris McCool +1
In this paper we propose a novel approach to multi-action recognition that performs joint segmentation and classification. This approach models each action using a Gaussian mixture…