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Augmentation is AUtO-Net: Augmentation-Driven Contrastive Multiview Learning for Medical Image Segmentation
The utilisation of deep learning segmentation algorithms that learn complex organs and tissue patterns and extract essential regions of interest from the noisy background to improve the visual ability for medical image diagnosis has achieved impressive results in Medical Image Computing (MIC).
Learning a Recurrent Residual Fusion Network for Multimodal Matching
A major challenge in matching between vision and language is that they typically have completely different features and representations.
On the Exploration of Convolutional Fusion Networks for Visual Recognition
Despite recent advances in multi-scale deep representations, their limitations are attributed to expensive parameters and weak fusion modules.
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