44 citations · 59 across the 3 of their papers we have counts for
7 papers
Unsupervised detection of mouse behavioural anomalies using two-stream convolutional autoencoders
Ezechukwu I Nwokedi, Rasneer S Bains, Luc Bidaut +3
This paper explores the application of unsupervised learning to detecting anomalies in mouse video data. The two models presented in this paper are a dual-stream, 3D convolutional…
DR-Unet104 for Multimodal MRI brain tumor segmentation
Jordan Colman, Lei Zhang, Wenting Duan +1
In this paper we propose a 2D deep residual Unet with 104 convolutional layers (DR-Unet104) for lesion segmentation in brain MRIs. We make multiple additions to the Unet architectu…
Automated Segmentation of Left Ventricle in 2D echocardiography using deep learning
Neda Azarmehr, Xujiong Ye, Faraz Janan +3
Following the successful application of the U-Net to medical images, there have been different encoder-decoder models proposed as an improvement to the original U-Net for segmentin…
MRI Brain Tumor Segmentation using Random Forests and Fully Convolutional Networks
Mohammadreza Soltaninejad, Lei Zhang, Tryphon Lambrou +3
In this paper, we propose a novel learning based method for automated segmentation of brain tumor in multimodal MRI images, which incorporates two sets of machine -learned and hand…
A hybrid model for predicting human physical activity status from lifelogging data
Ji Ni, Bowei Chen, Nigel M. Allinson +1
One trend in the recent healthcare transformations is people are encouraged to monitor and manage their health based on their daily diets and physical activity habits. However, muc…
Automatic individual pig detection and tracking in surveillance videos
Lei Zhang, Helen Gray, Xujiong Ye +2
Individual pig detection and tracking is an important requirement in many video-based pig monitoring applications. However, it still remains a challenging task in complex scenes, d…