Moreover, to exploit unlabelled source domain data—which tends to be much more plentiful than labelled data—we adopt a semi-supervised approach. We propose Velodrome, a semi-supervised method of out-of-distribution generalization that takes labelled and unlabelled data from different resources as ...
百度试题 结果1 题目In unsupervised learning our dataset is not labelled () . A. labelled B. unlabelled C. training D. untraining 相关知识点: 试题来源: 解析 B 反馈 收藏
}//Convert the labelled data to unlabelled dataUnlabelledClassificationData unlabelledData = classData.reformatAsUnlabelledClassificationData();//Train the Mixture Model for this classGaussianMixtureModels gaussianMixtureModel; gaussianMixtureModel.setMinChange( minChange ); gaussianMixtureModel.setMaxIter( max...
The training set consisted of both labelled and unlabelled images. We then leveraged a self-supervised learning technique to pretrain the AI model on the unlabelled images. Next, we fine-tuned the pretrained model on the labelled images. Results:When the images in the training dataset were ...
More specifically, we propose a computationally efficient self-supervised framework to create on-the-fly pseudo-labels for the unlabelled positive instances in the merged dataset in order to train the object detector jointly on both ground truth and pseudo labels. We evaluate our proposed framework ...
During experimentation, it has been observed that our proposed model, RGGCNN2, performs significantly better, both in grasping isolated objects as well as objects in a cluttered environment, compared to the existing approaches which do not use unlabelled data for generating grasping rectangles. To ...
Note that control groups of mice (i.e., mice without atherosclerosis injected with AuNP labelled monocytes and mice with atherosclerosis injected with unlabelled monocytes) were scanned with conventional CT, as previously published [32], where the specific imaging of AuNP labelled monocytes in ...