Results 21 to 30 of about 543,028 (283)
Audio self-supervised learning: A survey
Patterns, 2022 Inspired by the humans' cognitive ability to generalise knowledge and skills, Self-Supervised Learning (SSL) targets at discovering general representations from large-scale data without requiring human annotations, which is an expensive and time consuming task.
Shuo Liu +7 more
openaire +3 more sources
Siamese-Network Based Signature Verification using Self Supervised Learning
IJCCS (Indonesian Journal of Computing and Cybernetics Systems), 2023 The use of signatures is often encountered in various public documents ranging from academic documents to business documents that are a sign that the existence of signatures is crucial in various administrative processes.
Muhammad Fawwaz Mayda, Aina Musdholifah
doaj +1 more source
Remote Sensing, 2022 In recent years, supervised learning, represented by deep learning, has shown good performance in remote sensing image scene classification with its powerful feature learning ability. However, this method requires large-scale and high-quality handcrafted
Xiliang Chen, Guobin Zhu, Mingqing Liu
doaj +1 more source
Biased Self-supervised Learning for ASR
INTERSPEECH 2023, 2023 Self-supervised learning via masked prediction pre-training (MPPT) has shown impressive performance on a range of speech-processing tasks. This paper proposes a method to bias self-supervised learning towards a specific task. The core idea is to slightly finetune the model that is used to obtain the target sequence. This leads to better performance and
Kreyssig, Florian L. +5 more
openaire +2 more sources
Benchmarking the Semi-Supervised Naïve Bayes Classifier [PDF]
, 2015 Semi-supervised learning involves constructing predictive models with both labelled and unlabelled training data. The need for semi-supervised learning is driven by the fact that unlabelled data are often easy and cheap to obtain, whereas labelling data ...
Bagnall, Anthony +2 more
core +1 more source
Self-Supervised Learning for Cardiac MR Image Segmentation by Anatomical Position Prediction [PDF]
, 2019 In the recent years, convolutional neural networks have transformed the field of medical image analysis due to their capacity to learn discriminative image features for a variety of classification and regression tasks.
Bai, W. +8 more
core +4 more sources
Homomorphic Self-Supervised Learning
, 2022 In this work, we observe that many existing self-supervised learning algorithms can be both unified and generalized when seen through the lens of equivariant representations. Specifically, we introduce a general framework we call Homomorphic Self-Supervised Learning, and theoretically show how it may subsume the use of input-augmentations provided an ...
Keller, T. Anderson +2 more
openaire +2 more sources
Group-Based Siamese Self-Supervised Learning
Electronic Research Archive, 2023 <p>In this paper, we introduced a novel group self-supervised learning approach designed to improve visual representation learning. This new method aimed to rectify the limitations observed in conventional self-supervised learning. Traditional methods tended to focus on embedding distortion-invariant in single-view features.
Zhongnian Li +3 more
openaire +2 more sources
SSDL: Self-Supervised Dictionary Learning [PDF]
2021 IEEE International Conference on Multimedia and Expo (ICME), 2021 The label-embedded dictionary learning (DL) algorithms generate influential dictionaries by introducing discriminative information. However, there exists a limitation: All the label-embedded DL methods rely on the labels due that this way merely achieves ideal performances in supervised learning.
Shao, Shuai +5 more
openaire +2 more sources
Self-Supervised Node Classification with Strategy and Actively Selected Labeled Set
Entropy, 2022 To alleviate the impact of insufficient labels in less-labeled classification problems, self-supervised learning improves the performance of graph neural networks (GNNs) by focusing on the information of unlabeled nodes.
Yi Kang +3 more
doaj +1 more source