37 citations · 63 across the 15 of their papers we have counts for
4 papers · 1 filter
FocusNet++: Attentive Aggregated Transformations for Efficient and Accurate Medical Image Segmentation
Chaitanya Kaul, Nick Pears, Hang Dai +2
We propose a new residual block for convolutional neural networks and demonstrate its state-of-the-art performance in medical image segmentation. We combine attention mechanisms wi…
Penalizing small errors using an Adaptive Logarithmic Loss
Chaitanya Kaul, Nick Pears, Hang Dai +2
Loss functions are error metrics that quantify the difference between a prediction and its corresponding ground truth. Fundamentally, they define a functional landscape for travers…
SAWNet: A Spatially Aware Deep Neural Network for 3D Point Cloud Processing
Chaitanya Kaul, Nick Pears, Suresh Manandhar
Deep neural networks have established themselves as the state-of-the-art methodology in almost all computer vision tasks to date. But their application to processing data lying on…
FocusNet: An attention-based Fully Convolutional Network for Medical Image Segmentation
Chaitanya Kaul, Suresh Manandhar, Nick Pears
We propose a novel technique to incorporate attention within convolutional neural networks using feature maps generated by a separate convolutional autoencoder. Our attention archi…