Zobrazeno 1 - 10
of 747
pro vyhledávání: '"Global features"'
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-15 (2024)
Abstract With the population ages, many patients are unable to receive comprehensive care, leading to an increase in hazardous incidents, particularly falls occurring after getting out of bed. To address this issue, this paper proposes a method for r
Externí odkaz:
https://doaj.org/article/85380f34106d48acb14f6f62f1f13c26
Publikováno v:
IEEE Access, Vol 12, Pp 50935-50948 (2024)
In addressing the Flexible Job Shop Scheduling Problem (FJSP), deep reinforcement learning eliminates the need for mathematical modeling of the problem, requiring only interaction with the real environment to learn effective strategies. Using disjunc
Externí odkaz:
https://doaj.org/article/7fdc2daa9cc6486a861839326d7d260c
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 17, Pp 7475-7489 (2024)
Landslide susceptibility mapping (LSM) is a crucial step in quantitatively assessing landslide risk, essential for geologic hazards prevention. With the rapid development of deep learning models, convolutional neural networks (CNNs), and transformer
Externí odkaz:
https://doaj.org/article/20ec25cf173b43b39e8caeedfae34733
Publikováno v:
Complex & Intelligent Systems, Vol 10, Iss 2, Pp 2673-2688 (2023)
Abstract Despite the ability of 3D convolutional methods to extract spatio-temporal information simultaneously, they also increase parameter redundancy and computational and storage costs. Previous work that has utilized the 2D convolution method has
Externí odkaz:
https://doaj.org/article/e90db83461414c24b66e80685c50dff0
Publikováno v:
Sensors, Vol 24, Iss 19, p 6361 (2024)
Interactive image segmentation extremely accelerates the generation of high-quality annotation image datasets, which are the pillars of the applications of deep learning. However, these methods suffer from the insignificance of interaction informatio
Externí odkaz:
https://doaj.org/article/d7d51def441b41f08b7656df8e91067a
Publikováno v:
Journal of Marine Science and Engineering, Vol 12, Iss 9, p 1467 (2024)
Ocean exploration is crucial for utilizing its extensive resources. Images captured by underwater robots suffer from issues such as color distortion and reduced contrast. To address the issue, an innovative enhancement algorithm is proposed, which in
Externí odkaz:
https://doaj.org/article/bcf1059e05684967a4f70a31fcfe6547
Publikováno v:
Applied Sciences, Vol 14, Iss 17, p 7472 (2024)
Recently, convolutional neural networks (CNNs) and self-attention mechanisms have been widely applied in plant disease identification tasks, yielding significant successes. Currently, the majority of research models for tomato leaf disease recognitio
Externí odkaz:
https://doaj.org/article/ef9f9605e0cb42e58529b44f6b7eb54c
Publikováno v:
Computational Visual Media, Vol 9, Iss 4, Pp 657-685 (2023)
Abstract In the past ten years, research on face recognition has shifted to using 3D facial surfaces, as 3D geometric information provides more discriminative features. This comprehensive survey reviews 3D face recognition techniques developed in the
Externí odkaz:
https://doaj.org/article/497e7c47e2ef4d7688dd2531b29d0a7e
Autor:
Rong Tao
Publikováno v:
Applied Mathematics and Nonlinear Sciences, Vol 9, Iss 1 (2024)
This paper looks at 3D model retrieval techniques for digital virtual workshops in cloud computing. The global D2 shape distribution features are first used to sort the models for initial retrieval. Then the local curvature features are used to furth
Externí odkaz:
https://doaj.org/article/b177da501b8c431295804752f3e3d5bb
Publikováno v:
IEEE Access, Vol 11, Pp 38208-38217 (2023)
The overall purpose of this study is to propose a novel fine-tuning method for the CLIP architecture that enables the retention of pre-existing knowledge from large datasets and the creation of a domain-agnostic image encoder for universal image embe
Externí odkaz:
https://doaj.org/article/2b880768e8404191b7a6a66b99035513