Zobrazeno 1 - 10
of 858
pro vyhledávání: '"Self-supervision"'
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-11 (2024)
Abstract The existing deep estimation networks often overlook the issue of computational efficiency while pursuing high accuracy. This paper proposes a lightweight self-supervised network that combines convolutional neural networks (CNN) and Transfor
Externí odkaz:
https://doaj.org/article/461376c04c754c8d9d6cb0e65ac4e8cd
Publikováno v:
Acoustics, Vol 6, Iss 2, Pp 470-488 (2024)
Auditory research aims in general to lead to understanding of physiological processes. By contrast, the state of the art in automatic speech processing (notably recognition) is dominated by large pre-trained models that are meant to be used as black-
Externí odkaz:
https://doaj.org/article/f8ab2fc07df1468699804112c3c27e1c
Autor:
Pranav Singh, Raviteja Chukkapalli, Shravan Chaudhari, Luoyao Chen, Mei Chen, Jinqian Pan, Craig Smuda, Jacopo Cirrone
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-11 (2024)
Abstract Advancements in clinical treatment are increasingly constrained by the limitations of supervised learning techniques, which depend heavily on large volumes of annotated data. The annotation process is not only costly but also demands substan
Externí odkaz:
https://doaj.org/article/aab6c2c1aca247e8ab62a6ba1ddc8780
Autor:
Xiufeng Zhang, Haikuan Zhang, Haitao Li, Guoying Li, Shanshan Xue, Haichen Yin, Yang Chen, Fei Han
Publikováno v:
Frontiers in Earth Science, Vol 12 (2024)
The rockburst risk prediction based on microseismic (MS) data is an important research task in deep mine safety prevention. However, the lack of systematic research on explicit prediction indexes and the waste of a large amount of unlabeled data are
Externí odkaz:
https://doaj.org/article/c2b3ef98f83344aabff20aefd698feec
Publikováno v:
Heliyon, Vol 10, Iss 14, Pp e34726- (2024)
Cataracts are a leading cause of blindness worldwide, making accurate diagnosis and effective surgical planning critical. However, grading the severity of the lens nucleus is challenging because deep learning (DL) models pretrained using ImageNet per
Externí odkaz:
https://doaj.org/article/64f40f58971747da9767fbb23de88dbd
Publikováno v:
Geophysical Research Letters, Vol 51, Iss 12, Pp n/a-n/a (2024)
Abstract At mesoscale, trade wind clouds organize with various spatial arrangements, shaping their effect on Earth's energy budget. Representing their fine‐scale dynamics even at 1 km scale climate simulations remains challenging. However, geostati
Externí odkaz:
https://doaj.org/article/63afd1cfc0334c5fb9aee97fb37b9651
Publikováno v:
Jisuanji kexue yu tansuo, Vol 18, Iss 2, Pp 477-485 (2024)
In view of the catastrophic forgetting phenomenon of knowledge in class incremental learning in image classification, the existing class incremental learning methods focus on the correction of the unbalanced offset of the model classification layer,
Externí odkaz:
https://doaj.org/article/f97a81c869f541c6bbacfa6c247713ec
Autor:
Sadjad Rezvani, Fatemeh Soleymani Siahkar, Yasin Rezvani, Abdorreza Alavi Gharahbagh, Vahid Abolghasemi
Publikováno v:
IEEE Access, Vol 12, Pp 121077-121092 (2024)
Restoring a high-quality image from a noisy version poses a significant challenge in computer vision, particularly in today’s context where high-resolution and large-sized images are prevalent. As such, fast and efficient techniques are required to
Externí odkaz:
https://doaj.org/article/87107460d3b94aff933c82501a5c1f27
Publikováno v:
IEEE Access, Vol 12, Pp 53565-53578 (2024)
In this paper we delve into the properties of transformers, attained through self-supervision, in the point cloud domain. Specifically, we evaluate the effectiveness of Masked Autoencoding as a pretraining scheme, and explore Momentum Contrast as an
Externí odkaz:
https://doaj.org/article/7991a5d8f43b42a9877f8e61290b612e
Publikováno v:
Applied Sciences, Vol 14, Iss 17, p 8054 (2024)
Engineering vehicles play a vital role in supporting construction projects. However, due to their substantial size, heavy tonnage, and significant blind spots while in motion, they present a potential threat to road maintenance, pedestrian safety, an
Externí odkaz:
https://doaj.org/article/d5b8901483af41d0a74bae6e74a05eda