Results 31 to 40 of about 490,549 (310)
Mixup Feature: A Pretext Task Self-Supervised Learning Method for Enhanced Visual Feature Learning
IEEE Access, 2023 Self-supervised learning has emerged as an increasingly popular research topic within the field of computer vision. In this study, we propose a novel self-supervised learning approach based on Mixup features as pretext tasks.
Jiashu Xu, Sergii Stirenko
doaj +1 more source
Self-directed multimodal learning in higher education [PDF]
, 2020 This book aims to provide an overview of theoretical and practical considerations in terms of self-directed multimodal learning within the university context.
Bailey, Roxanne +9 more
core +1 more source
Adversarial Masking for Self-Supervised Learning
CoRR, 2022 We propose ADIOS, a masked image model (MIM) framework for self-supervised learning, which simultaneously learns a masking function and an image encoder using an adversarial objective. The image encoder is trained to minimise the distance between representations of the original and that of a masked image.
Shi, Yuge +3 more
openaire +5 more sources
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
Learning through assessment [PDF]
, 2021 This book aims to contribute to the discourse of learning through assessment within a self-directed learning environment. It adds to the scholarship of assessment and self-directed learning within a face-to-face and online learning environment.
Mentz, Elsa +13 more
core +1 more source
On the Stepwise Nature of Self-Supervised Learning
CoRR, 2023 9 pages (main text) + 14 pages (refs + appendices).
James B. Simon +5 more
openaire +3 more sources
Monocular obstacle avoidance with persistent Self-Supervised Learning [PDF]
, 2014 Raw data belonging to paper: Persistent self-supervised learning: from stereo to monocular vision for obstacle ...
van Hecke, K.G. (Kevin)
core +1 more source
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
PackerRobo: Model-based robot vision self supervised learning in CART
Alexandria Engineering Journal, 2022 Robots are most widely used to replace human contribution with machine generated response. When humans interact with robots, its mandatory for both to forecast actions based on current conditions. Huge efforts have been channelized towards attaining this
Asif Khan +8 more
doaj +1 more source
Mean Shift for Self-Supervised Learning [PDF]
2021 IEEE/CVF International Conference on Computer Vision (ICCV), 2021 Most recent self-supervised learning (SSL) algorithms learn features by contrasting between instances of images or by clustering the images and then contrasting between the image clusters. We introduce a simple mean-shift algorithm that learns representations by grouping images together without contrasting between them or adopting much of prior on the ...
Soroush Abbasi Koohpayegani +2 more
openaire +2 more sources