Results 41 to 50 of about 543,028 (283)

Self-supervised learning methods and applications in medical imaging analysis: a survey [PDF]

PeerJ Computer Science, 2022
The scarcity of high-quality annotated medical imaging datasets is a major problem that collides with machine learning applications in the field of medical imaging analysis and impedes its advancement.
Saeed Shurrab, Rehab Duwairi
doaj   +2 more sources

Self‐supervised learning with randomised layers for remote sensing

Electronics Letters, 2021
This letter presents a new self‐supervised learning approach based on randomised layers for remote sensing. Our method is basically based on the Tile2Vec approach, which is one of the state‐of‐the‐art self‐supervised learning approaches for remote ...
Heechul Jung, Taegyun Jeon
doaj   +1 more source

Multi-task Self-Supervised Visual Learning [PDF]

2017 IEEE International Conference on Computer Vision (ICCV), 2017
Published at ICCV ...
Doersch, C, Zisserman, A
openaire   +3 more sources

Self-Supervised Learning for Solar Radio Spectrum Classification

Universe, 2022
Solar radio observation is an important way to study the Sun. Solar radio bursts contain important information about solar activity. Therefore, real-time automatic detection and classification of solar radio bursts are of great value for subsequent solar
Siqi Li, Guowu Yuan, Jian Chen, Chengming Tan, Hao Zhou   +4 more
doaj   +1 more source

Discovering Lin-Kernighan-Helsgaun heuristic for routing optimization using self-supervised reinforcement learning

Journal of King Saud University: Computer and Information Sciences, 2023
Vehicle routing optimization is a crucial responsibility of transportation service providers, which can significantly reduce operating expenses and improve client satisfaction.
Qi Wang, Chengwei Zhang, Chunlei Tang
doaj   +1 more source

Improving drug–target affinity prediction by adaptive self-supervised learning [PDF]

PeerJ Computer Science
Computational drug-target affinity prediction is important for drug screening and discovery. Currently, self-supervised learning methods face two major challenges in drug-target affinity prediction.
Qing Ye, Yaxin Sun
doaj   +2 more sources

Self-Supervised Learning for the Distinction between Computer-Graphics Images and Natural Images

Applied Sciences, 2023
With the increasing visual realism of computer-graphics (CG) images generated by advanced rendering engines, the distinction between CG images and natural images (NIs) has become an important research problem in the image forensics community.
Kai Wang
doaj   +1 more source

X-ray modalities in the era of artificial intelligence: overview of self-supervised learning approach

FACETS
Self-supervised learning enables the creation of algorithms that outperform supervised pre-training methods in numerous computer vision tasks. This paper provides a comprehensive overview of self-supervised learning applications across various X-ray ...
Ivan Martinović, Shitong Mao, Mehdy Dousty, Wuqi Li, Milena Đukanović, Errol Colak, Ervin Sejdić   +6 more
doaj   +1 more source

Experimental Case Study of Self-Supervised Learning for Voice Spoofing Detection

IEEE Access, 2023
This study aims to improve the performance of voice spoofing attack detection through self-supervised pre-training. Supervised learning needs appropriate input variables and corresponding labels for constructing the machine learning models that are to be
Yerin Lee, Narin Kim, Jaehong Jeong, Il-Youp Kwak   +3 more
doaj   +1 more source

Transitive Invariance for Self-supervised Visual Representation Learning

, 2017
Learning visual representations with self-supervised learning has become popular in computer vision. The idea is to design auxiliary tasks where labels are free to obtain.
Gupta, Abhinav, He, Kaiming, Wang, Xiaolong   +2 more
core   +1 more source