This paper propose a data augmentation method for medical images. Only one annotated image (x, l) is used as reference atlas and other unlabeled images, e.g., y1,y2,...ym are used to learn transforms between the atlas x and y1,y2,..,ym. Once the transforms are learned, the author...
Table 3 The performance of different methods in image segmentation. Full size table Finally, we explored the use of a simulated dataset as data augmentation to replace the real dataset for training a neural network. As shown in Table3, using the same real test set initially separated out from...
In such kind of problems the data deficiency is one of the most relevant issues. Finally, we discuss the advantages and disadvantages of the methods being analyzed. 展开 关键词: Machine learning style transfer data augmentation deep learning medical imaging 被引量: 4 ...
A comparison of streaming models and data augmentation methods for robust speech recognition 本文为三星在2021.11.19更新的文章,主要对比端到端流式ASR系统Monotonic Chunkwise Attention (MoChA) 和 Recurrent Neural Network-Transducer (RNN-T)的性能以及multi-conditioned training using an acoustic simulator, Vocal...
Unfortunately, current methods are mostly developed for high-level vision tasks (e.g., classification) and few are studied for low-level vision tasks (e.g., image restoration). In this paper, we provide a comprehensive analysis of the existing augmentation methods applied to the super-...
Nevertheless, these methods do not essentially increase the quality of the dataset. A novel data augmentation strategy was thus proposed in this study by using simulated remote sensing ship images to augment the positive training samples. The simulated images are generated by true background images ...
For my dataset I could only set it to 1, so this really depends on your data. 2nd augmentation technique: noise introduction We can either remove black pixels or add white pixels to the image. there are several methods to that. I have experimented with many of them, but here is my sho...
Natural Language Processing (NLP) is one of the most captivating applications of Deep Learning. In this survey, we consider how the Data Augmentation training strategy can aid in its development. We begin with the major motifs of Data Augmentation summar
New methods like augmix,cutmix,are being tracked. Whether you're a researcher or an engineer, just enjoy it! Popular Projects imgaug intro: 2019 github star: 7.8k github: https://github.com/aleju/imgaug Albumentations Albumentations: fast and flexible image augmentations intro: ArXiv 2018 ...
This improvement compares favorably to state-of-the-art augmentation methods for natural images. Through an ablative test, augmentation is also shown to substantively improve performance when applied before hyperparameter optimization. These results suggest the optimal order of operations and support the ...