Zobrazeno 1 - 10
of 336
pro vyhledávání: '"GARIBALDI Jonathan M"'
ESP-MedSAM: Efficient Self-Prompting SAM for Universal Domain-Generalized Medical Image Segmentation
Autor:
Xu, Qing, Li, Jiaxuan, He, Xiangjian, Liu, Ziyu, Chen, Zhen, Duan, Wenting, Li, Chenxin, He, Maggie M., Tesema, Fiseha B., Cheah, Wooi P., Wang, Yi, Qu, Rong, Garibaldi, Jonathan M.
The universality of deep neural networks across different modalities and their generalization capabilities to unseen domains play an essential role in medical image segmentation. The recent Segment Anything Model (SAM) has demonstrated its potential
Externí odkaz:
http://arxiv.org/abs/2407.14153
Publikováno v:
智能科学与技术学报, Vol 1, Pp 319-326 (2019)
As a decision support system,fuzzy system can deal with uncertainty and has a clear representation of uncertainty knowledge and inference process.But one problem that exists is that computerized decision support systems,including systems that use fuz
Externí odkaz:
https://doaj.org/article/5131bfe96ed745119f91355baaecbd0d
Publikováno v:
智能科学与技术学报, Vol 1, Iss 4, Pp 319-326 (2019)
作为一种决策支持系统，模糊系统不仅具有处理不确定性信息的能力，又能够明确表达不确定性知识和推理过程。但现存的一个问题是，对于包括采用模糊方法的系统在内的计算机决策支持
Externí odkaz:
https://doaj.org/article/61ffcb9a2a0647f39e711d7c39e77ea7
Since their introduction, fuzzy sets and systems have become an important area of research known for its versatility in modelling, knowledge representation and reasoning, and increasingly its potential within the context explainable AI. While the app
Externí odkaz:
http://arxiv.org/abs/2403.12308
Publikováno v:
Remote Sens. 2022, 14, 3361
In supervised deep learning, learning good representations for remote--sensing images (RSI) relies on manual annotations. However, in the area of remote sensing, it is hard to obtain huge amounts of labeled data. Recently, self--supervised learning s
Externí odkaz:
http://arxiv.org/abs/2107.05948
Publikováno v:
In Information Sciences March 2024 661
This paper presents a novel meta learning framework for feature selection (FS) based on fuzzy similarity. The proposed method aims to recommend the best FS method from four candidate FS methods for any given dataset. This is achieved by firstly const
Externí odkaz:
http://arxiv.org/abs/2005.09856
In this paper, we propose a novel weighted combination feature selection method using bootstrap and fuzzy sets. The proposed method mainly consists of three processes, including fuzzy sets generation using bootstrap, weighted combination of fuzzy set
Externí odkaz:
http://arxiv.org/abs/2005.05003
In this paper, based on a fuzzy entropy feature selection framework, different methods have been implemented and compared to improve the key components of the framework. Those methods include the combinations of three ideal vector calculations, three
Externí odkaz:
http://arxiv.org/abs/2005.04888
Publikováno v:
BMC Bioinformatics, Vol 10, Iss 1, p 358 (2009)
Abstract Background Statistical analysis of DNA microarray data provides a valuable diagnostic tool for the investigation of genetic components of diseases. To take advantage of the multitude of available data sets and analysis methods, it is desirab
Externí odkaz:
https://doaj.org/article/2e9e9f4b9f9e40ea916dafa117999cab