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10 papers · 2 filters
Medical Visual Question Answering: A Survey
Zhihong Lin, Donghao Zhang, Qingyi Tao +5
Medical Visual Question Answering~(VQA) is a combination of medical artificial intelligence and popular VQA challenges. Given a medical image and a clinically relevant question in…
See Eye to Eye: A Lidar-Agnostic 3D Detection Framework for Unsupervised Multi-Target Domain Adaptation
Darren Tsai, Julie Stephany Berrio, Mao Shan +2
Sampling discrepancies between different manufacturers and models of lidar sensors result in inconsistent representations of objects. This leads to performance degradation when 3D…
Automated Aerial Animal Detection When Spatial Resolution Conditions Are Varied
Jasper Brown, Yongliang Qiao, Cameron Clark +3
Knowing where livestock are located enables optimized management and mustering. However, Australian farms are large meaning that many of Australia's livestock are unmonitored which…
GeoCLR: Georeference Contrastive Learning for Efficient Seafloor Image Interpretation
Takaki Yamada, Adam Prügel-Bennett, Stefan B. Williams +2
This paper describes Georeference Contrastive Learning of visual Representation (GeoCLR) for efficient training of deep-learning Convolutional Neural Networks (CNNs). The method le…
Reading Race: AI Recognises Patient's Racial Identity In Medical Images
Imon Banerjee, Ananth Reddy Bhimireddy, John L. Burns +20
Background: In medical imaging, prior studies have demonstrated disparate AI performance by race, yet there is no known correlation for race on medical imaging that would be obviou…
Unsupervised Scale-consistent Depth Learning from Video
Jia-Wang Bian, Huangying Zhan, Naiyan Wang +5
We propose a monocular depth estimator SC-Depth, which requires only unlabelled videos for training and enables the scale-consistent prediction at inference time. Our contributions…