Few-shot learningMeta-learningMulti-shot learningMedical image classificationImage augmentationHistopathological image classificationThe occurrence of long-tailed distributions and unavailability of high-quality annotated images is a common phenomenon in medical datasets. The use of conventional Deep Learning ...
摘要: Rapid and accurate classification of medical images plays an important role in medical diagnosis. Nowadays, for medical image classification, there are some methods based on machine learning, deep...关键词: Medical image classification Few-shot learning Attention mechanism Transfer learning ...
Liu X, Liu P, Zong L (2020) Transductive prototypical network for few-shot classification. IEEE Int Conf Image Process (ICIP) 2020:1671–1675. https://doi.org/10.1109/ICIP40778.2020.9191037 Article Google Scholar Matarneh ST, Danso-Amoako M, Al-Bizri S, Gaterell M, Matarneh R (2019...
本文是 MIT CSAIL & Google Research 在2020年关于 Few-Shot Learning的又一篇力作,受 ICLR 2020 的经典文章 A baseline for few-shot image classification 启发,提出了如下假设: Embeddings are the most critical factor to the performance of few-shot learning/meta learning algorithms; better embeddings wi...
(2019). A baseline for few-shot image classification. In International Conference on Learning Representations 2020. ArXiv, abs/1909.02729. Google Scholar London, A. (2019). Artificial intelligence and black-box medical decisions: accuracy versus explainability. The Hastings Center Report, 49, 15–...
Deep metric learning for few-shot image classification: A Review of recent developments 2023, Pattern Recognition Show abstract Recent advances and clinical applications of deep learning in medical image analysis 2022, Medical Image Analysis Show abstract Segmentation information with attention integration fo...
In this paper, a pairwise-based meta learning(PML) method is proposed for few-shot image classification. Transitive transfer learning is used to fine tune the pre-trained Resnet50 model to get a feature encoder that is more suitable for few shot task. Th
大家好!这里介绍一下我们在ICML 2022中稿的一篇论文,主题和去年我们的NeurIPS论文一样,仍然是few-shot image classification/transfer,但这次的研究比之前更为深入,发现了特征表示的channel bias问题,可以算是挖到了当前视觉模型表示学习的一个核心问题。 一句话总结 ...
IP属地: 福建 0.1592022.02.21 16:01:36字数 871阅读 790 Hello~ 两个月没更新啦 年都过了 虎年大吉呀大家 把剩下的一点关于小样本学习的论文阅读更新完~ 后续就是随缘更新啦 有需要交流可以简信啦 论文名称: 《few-shot image classification with multi-facet prototypes》 ...
借鉴《Automated human cell classification in sparse datasets using few-shot learning》这篇文章,大概了解了few-shot learning的一些模型。这篇文章于2022.2.21发表在scientific reports上,是Nature的 子刊,综合3区,3年平均IF为4.13。 本文第一部分会介绍一下这篇文章, ...