Results 61 to 70 of about 10,284,296 (292)
Generative knowledge-based transfer learning for few-shot health condition estimation
Complex & Intelligent Systems, 2022 In the field of high-end manufacturing, it is valuable to study few-shot health condition estimation. Although transfer learning and other methods have effectively improved the ability of few-shot learning, they still cannot solve the lack of prior ...
Weijie Kang, Jiyang Xiao, Junjie Xue
doaj +1 more source
A Contrastive Model with Local Factor Clustering for Semi-Supervised Few-Shot Learning
Mathematics, 2023 Learning novel classes with a few samples per class is a very challenging task in deep learning. To mitigate this issue, previous studies have utilized an additional dataset with extensively labeled samples to realize transfer learning.
Hexiu Lin +3 more
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Pixels to pitch: extending few-shot learning to audio tasks [PDF]
Few-Shot Learning has gained significant attention in recent years as a possible tool for solving tasks which have too little data for traditional machine learning pipelines, such as user adaptable AI systems or rare event detection. At the start of this
Heggan, Calum
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A survey of few-shot learning in smart agriculture: developments, applications, and challenges
Plant Methods, 2022 With the rise of artificial intelligence, deep learning is gradually applied to the field of agriculture and plant science. However, the excellent performance of deep learning needs to be established on massive numbers of samples.
Jiachen Yang +5 more
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Molecular Oncology, EarlyView.Matched spatial transcriptomics and single‐nuclei RNA‐seq were generated for anaplastic and BRAFV600E papillary thyroid cancers revealing generic and tumor‐specific states occurring in cancer cells and in the tumor microenvironment. In this context, cancer dedifferentiation mirrored organoid maturation through ordered thyroid marker gain/loss ...
Adrien Tourneur +11 more
wiley +1 more source
Dual Prototype Learning for Few Shot Semantic Segmentation
IEEE AccessFew-shot segmentation (FSS) is a challenging task because the same class of targets in the support and query images may have different scales, textures and background information.
Wenxuan Li, Shaobo Chen, Chengyi Xiong
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Multimodal Few-Shot Learning for Gait Recognition
Applied Sciences, 2020 A person’s gait is a behavioral trait that is uniquely associated with each individual and can be used to recognize the person. As information about the human gait can be captured by wearable devices, a few studies have led to the proposal of methods to ...
Jucheol Moon +3 more
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Active Instance Selection for Few-Shot Classification
IEEE Access, 2022 Few-shot learning aims to develop well-trained models by using only a few annotated samples. However, the performance of few-shot learning deteriorates if inappropriate support samples are selected.
Junsup Shin +3 more
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Few-shot Learning with Noisy Labels
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022 Accepted to CVPR ...
Kevin J. Liang +3 more
openaire +2 more sources
The impact of leukocyte‐associated RNA retention on platelet RNA‐based cancer detection
Molecular Oncology, EarlyView.Platelets carry RNA signals that may help detect cancer, but platelet samples can also retain RNA from white blood cells. We found that this retained white blood cell signal did not significantly affect machine learning cancer classification, suggesting that the cancer‐related RNA signal in platelets is largely independent of leukocyte‐associated RNA ...
Michał Sieczczyński +12 more
wiley +1 more source