Results 21 to 30 of about 5,879,357 (336)
IET Cyber-systems and Robotics, 2022 Particle image velocimetry (PIV) is an essential method in experimental fluid dynamics. In recent years, the development of deep learning‐based methods has inspired new approaches to tackle the PIV problem, which considerably improves the accuracy of PIV.
Yiwei Chong +4 more
doaj +1 more source
A Large-Scale Study on Unsupervised Spatiotemporal Representation Learning [PDF]
Computer Vision and Pattern Recognition, 2021 We present a large-scale study on unsupervised spatiotemporal representation learning from videos. With a unified perspective on four recent image-based frameworks, we study a simple objective that can easily generalize all these methods to space-time ...
Christoph Feichtenhofer +4 more
semanticscholar +1 more source
Stable and Fast Deep Mutual Information Maximization Based on Wasserstein Distance
Entropy, 2023 Deep learning is one of the most exciting and promising techniques in the field of artificial intelligence (AI), which drives AI applications to be more intelligent and comprehensive.
Xing He +4 more
doaj +1 more source
An Unsupervised Machine Learning Algorithms: Comprehensive Review
International Journal of Computing and Digital Systems, 2023 : Machine learning (ML) is a data-driven strategy in which computers learn from data without human intervention. The outstanding ML applications are used in a variety of areas.
Samreen Naeem +3 more
semanticscholar +1 more source
Unsupervised Prompt Learning for Vision-Language Models [PDF]
arXiv.org, 2022 Contrastive vision-language models like CLIP have shown great progress in transfer learning. In the inference stage, the proper text description, also known as prompt, needs to be carefully designed to correctly classify the given images.
Hao Huang, Jack Chu, Fangyun Wei
semanticscholar +1 more source
Unsupervised Learning of Monocular Depth Estimation:A Survey [PDF]
Jisuanji kexueAs the key point of 3D reconstruction,automatic driving and visual SLAM,depth estimation has always been a hot research direction in the field of computer vision,among which,monocular depth estimation technology based on unsupervised learning has been ...
CAI Jiacheng, DONG Fangmin, SUN Shuifa, TANG Yongheng
doaj +1 more source
Classification under Streaming Emerging New Classes: A Solution using Completely Random Trees [PDF]
, 2016 This paper investigates an important problem in stream mining, i.e., classification under streaming emerging new classes or SENC. The common approach is to treat it as a classification problem and solve it using either a supervised learner or a semi ...
Mu, Xin, Ting, Kai Ming, Zhou, Zhi-Hua
core +3 more sources
DeConFuse: a deep convolutional transform-based unsupervised fusion framework
EURASIP Journal on Advances in Signal Processing, 2020 This work proposes an unsupervised fusion framework based on deep convolutional transform learning. The great learning ability of convolutional filters for data analysis is well acknowledged.
Pooja Gupta +4 more
doaj +1 more source
Proceedings of the National Academy of Sciences of the United States of America, 2019 Significance Learning biological properties from sequence data is a logical step toward generative and predictive artificial intelligence for biology.
Alexander Rives +7 more
semanticscholar +1 more source
Unsupervised Cross-lingual Representation Learning for Speech Recognition [PDF]
Interspeech, 2020 This paper presents XLSR which learns cross-lingual speech representations by pretraining a single model from the raw waveform of speech in multiple languages.
Alexis Conneau +4 more
semanticscholar +1 more source