Results 51 to 60 of about 543,028 (283)
Self-Supervised Video Similarity Learning
2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), 2023 We introduce S$^2$VS, a video similarity learning approach with self-supervision. Self-Supervised Learning (SSL) is typically used to train deep models on a proxy task so as to have strong transferability on target tasks after fine-tuning. Here, in contrast to prior work, SSL is used to perform video similarity learning and address multiple retrieval ...
Kordopatis-Zilos, Giorgos +5 more
openaire +2 more sources
Semi-Supervised Self-Taught Deep Learning for Finger Bones Segmentation
, 2019 Segmentation stands at the forefront of many high-level vision tasks. In this study, we focus on segmenting finger bones within a newly introduced semi-supervised self-taught deep learning framework which consists of a student network and a stand-alone ...
Chen, Cen +8 more
core +1 more source
Self-Supervised Representation Learning for Ultrasound Video
2020 IEEE 17th International Symposium on Biomedical Imaging (ISBI), 2020 Recent advances in deep learning have achieved promising performance for medical image analysis, while in most cases ground-truth annotations from human experts are necessary to train the deep model. In practice, such annotations are expensive to collect and can be scarce for medical imaging applications.
Jaio, J +4 more
openaire +4 more sources
Self-Writer: Clusterable Embedding Based Self-Supervised Writer Recognition from Unlabeled Data
Mathematics, 2022 Writer recognition based on a small amount of handwritten text is one of the most challenging deep learning problems because of the implicit characteristics of handwriting styles.
Zabir Mohammad +4 more
doaj +1 more source
Time-Contrastive Networks: Self-Supervised Learning from Video
, 2018 We propose a self-supervised approach for learning representations and robotic behaviors entirely from unlabeled videos recorded from multiple viewpoints, and study how this representation can be used in two robotic imitation settings: imitating object ...
Chebotar, Yevgen +6 more
core +1 more source
Self-Supervised Adversarial Imitation Learning
2023 International Joint Conference on Neural Networks (IJCNN), 2023 This paper has been accepted in the International Joint Conference on Neural Networks (IJCNN ...
Monteiro, Juarez +3 more
openaire +2 more sources
To Compress or Not to Compress—Self-Supervised Learning and Information Theory: A Review
EntropyDeep neural networks excel in supervised learning tasks but are constrained by the need for extensive labeled data. Self-supervised learning emerges as a promising alternative, allowing models to learn without explicit labels.
Ravid Shwartz Ziv, Yann LeCun
doaj +1 more source
Self-Supervised EEG Emotion Recognition Models Based on CNN
IEEE Transactions on Neural Systems and Rehabilitation Engineering, 2023 Emotion plays crucial roles in human life. Recently, emotion classification from electroencephalogram (EEG) signal has attracted attention by researchers due to the rapid development of brain computer interface (BCI) techniques and machine learning ...
Xingyi Wang +5 more
doaj +1 more source
CASSL: Curriculum Accelerated Self-Supervised Learning
, 2018 Recent self-supervised learning approaches focus on using a few thousand data points to learn policies for high-level, low-dimensional action spaces.
Gandhi, Dhiraj +3 more
core +1 more source
Self-Supervised Ranking for Representation Learning
, 2020 We present a new framework for self-supervised representation learning by formulating it as a ranking problem in an image retrieval context on a large number of random views (augmentations) obtained from images. Our work is based on two intuitions: first, a good representation of images must yield a high-quality image ranking in a retrieval task ...
Varamesh, Ali +3 more
openaire +3 more sources