Results 11 to 20 of about 520,684 (243)
Journal of Applied Clinical Medical Physics, Volume 23, Issue 12, December 2022., 2022 Abstract Positron emission tomography with x‐ray computed tomography (PET/CT) is increasingly being utilized for radiation treatment planning (RTP). Accurate delivery of RT therefore depends on quality PET/CT data. This study covers quality control (QC) procedures required for PET/CT for diagnostic imaging and incremental QC required for RTP.
Ran Klein +7 more
wiley +1 more source
Non-contrastive sentence representations via self-supervision [PDF]
arXiv, 2023 Sample contrastive methods, typically referred to simply as contrastive are the foundation of most unsupervised methods to learn text and sentence embeddings. On the other hand, a different class of self-supervised loss functions and methods have been considered in the computer vision community and referred to as dimension contrastive.
arxiv
Contrastive Domain Adaptation [PDF]
Proceedings of the IEEE/CVF Conference on Computer Vision and
Pattern Recognition (CVPR) Workshops, 2021, pp. 2209-2218, 2021 Recently, contrastive self-supervised learning has become a key component for learning visual representations across many computer vision tasks and benchmarks. However, contrastive learning in the context of domain adaptation remains largely underexplored.
arxiv
Contrastive Representation Learning: A Framework and Review [PDF]
, 2020 Contrastive Learning has recently received interest due to its success in self-supervised representation learning in the computer vision domain. However, the origins of Contrastive Learning date as far back as the 1990s and its development has spanned across many fields and domains including Metric Learning and natural language processing.
arxiv +1 more source
UniCLIP: Unified Framework for Contrastive Language-Image Pre-training [PDF]
arXiv, 2022 Pre-training vision-language models with contrastive objectives has shown promising results that are both scalable to large uncurated datasets and transferable to many downstream applications. Some following works have targeted to improve data efficiency by adding self-supervision terms, but inter-domain (image-text) contrastive loss and intra-domain ...
arxiv
Acuity and contrast sensivity of infant vision
Nature, 1974 IF we are to study the development of form and space perception in man, it is necessary to know something of the basic visual capabilities of the developing human infant. There have been a number of investigations of visual acuity in the first few months of life.
Atkinson, J, Braddick, O, Braddick, F
openaire +4 more sources
A review of artificial intelligence in brachytherapy
Journal of Applied Clinical Medical Physics, EarlyView.Abstract Artificial intelligence (AI) has the potential to revolutionize brachytherapy's clinical workflow. This review comprehensively examines the application of AI, focusing on machine learning and deep learning, in various aspects of brachytherapy.
Jingchu Chen +4 more
wiley +1 more source
Tracking without Label: Unsupervised Multiple Object Tracking via Contrastive Similarity Learning [PDF]
arXiv, 2023 Unsupervised learning is a challenging task due to the lack of labels. Multiple Object Tracking (MOT), which inevitably suffers from mutual object interference, occlusion, etc., is even more difficult without label supervision. In this paper, we explore the latent consistency of sample features across video frames and propose an Unsupervised ...
arxiv
Effects of Contrast Sensitivity on Colour Vision Testing [PDF]
Neuro-Ophthalmology, 2017 This study analyses how contrast sensitivity loss affects colour vision (CV) testing. Eleven participants were scored while cycling through randomly arranged pictures of CV tests with varying levels of contrast changes applied. Hardy-Rand-Rittler (HRR) scores declined significantly at each successive decrease in contrast level after the highest setting
Anvesh Annadanam +3 more
openaire +2 more sources
Amygdala Neurodegeneration: A Key Driver of Visual Dysfunction in Parkinson's Disease
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective Visual disability in Parkinson's disease (PD) is not fully explained by retinal neurodegeneration. We aimed to delineate the brain substrate of visual dysfunction in PD and its association with retinal thickness. Methods Forty‐two PD patients and 29 controls underwent 3‐Tesla MRI, retinal spectral‐domain optical coherence tomography,
Asier Erramuzpe +15 more
wiley +1 more source