论文笔记7:Knowledge-enhanced visual-language pre-training on chest radiology images juezhi 创作声明:包含 AI 辅助创作 1 人赞同了该文章 目录 收起 1 概览 2 Introduction 3 Related Work 4 Method 4.1 算法概述 4.2 问题场景 4.3 Knowledge encoder 4.4 Entity extraction 4.5 Knowledge-guided visual...
While multi-modal foundation models pre-trained on large-scale data have been successful in natural language understanding and vision recognition, their use in medical domains is still limited due to the fine-grained nature of medical tasks and the high demand for domain knowledge. To address this...
While multi-modal foundation models pre-trained on large-scale data have been successful in natural language understanding and vision recognition, their use in medical domains is still limited due to the fine-grained nature of medical tasks and the high demand for domain knowledge. To address this...
In this paper, we consider the problem of enhancing self-supervised visual-language pre-training (VLP) with medical-specific knowledge, by exploiting the paired image-text reports from the radiological daily practice. In particular, we make the following contributions 在本文中,我们考虑了增强自我监督...
一个突出的模型是VisualBERT [48][Visualbert: A simple and performant baseline for vision and language],它倾向于将BERT架构纳入视觉信息。它利用大规模图像-文本数据集的预训练来共同学习视觉和文本模态的表示。VisualBERT通过利用大规模图像标题数据来学习对齐图像和文本。它使用屏蔽的令牌预测任务,其中视觉和文本...
Learning transferable visual models from natural language supervision. In Marina Meila and Tong Zhang, editors, Proceedings of the 38th Interna- tional Conference on Machine Learning, ICML 2021, 18-24 July 2021, Virtual Event, volume 139 of Proceedings...
Existing works have attained partial success by extensively leveraging various sources of information available in the datasets, such as heavy intermediate visual observations, procedural names, or natural language step-by-step instructions, for features or supervision signals. However, the task remains ...
VCD: Mitigating Object Hallucinations in Large Vision-Language Models through Visual Contrastive Decoding CAL: Prioritizing Visual Correlation by Contrastive Alignment About Official PyTorch Implementation of MLLM Is a Strong Reranker: Advancing Multimodal Retrieval-augmented Generation via Knowledge-enhanced Re...
propose to enhance the item representations with the structural, textual and visual knowledge extracted from the knowledge base [12], and Wang et al. propose an end-to-end framework to perform explicit reasoning on KG to learn path semantics and improve the recommendation interpretability [18]. ...
1. Visual: Definition: Learners who prefer to learn through visual representations such as images, diagrams, graphs, and videos. They excel at processing information through sight and retain knowledge by visualizing concepts. Strengths: Excellent at remembering images, diagrams, and spatial relations...