323 citations · 2k across the 63 of their papers we have counts for
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Fine-Grained Classification via Mixture of Deep Convolutional Neural Networks
ZongYuan Ge, Alex Bewley, Christopher McCool +3
We present a novel deep convolutional neural network (DCNN) system for fine-grained image classification, called a mixture of DCNNs (MixDCNN). The fine-grained image classification…
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…