Zobrazeno 1 - 10
of 3 384
pro vyhledávání: '"Weakly supervised learning"'
Autor:
Xin Yao
Publikováno v:
Computational Urban Science, Vol 4, Iss 1, Pp 1-13 (2024)
Abstract Point-of-interest (POI) is a fundamental data type of maps. Anomalous POIs would make maps outdated and lead to user-unfriendly location-based services, and thus should be discovered as fast as possible. Traditional POI anomaly detection met
Externí odkaz:
https://doaj.org/article/36c12f24a93c45aa91daac55407f1085
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-13 (2024)
Abstract Chest X-ray is widely used to diagnose lung diseases. Due to the demand for accelerating analysis and interpretation to reduce the workload of radiologists, there has been a growing interest in building automated systems of chest X-ray abnor
Externí odkaz:
https://doaj.org/article/cb3a4fc88ff34d81b1aa750d3700399e
Publikováno v:
Molecular Oncology, Vol 18, Iss 11, Pp 2755-2769 (2024)
Early cancer diagnosis from bisulfite‐treated cell‐free DNA (cfDNA) fragments requires tedious data analytical procedures. Here, we present a deep‐learning‐based approach for early cancer interception and diagnosis (DECIDIA) that can achieve
Externí odkaz:
https://doaj.org/article/cc67456d0b304a818b85b00963dc4443
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-14 (2024)
Abstract Visual observing muscle tissue regeneration is used to measure experimental effect size in biological research to discover the mechanism of muscle strength decline due to illness or aging. Quantitative computer imaging analysis for support e
Externí odkaz:
https://doaj.org/article/6d43f7088d2a4139b2d617e9420d63db
Publikováno v:
International Journal of Digital Earth, Vol 17, Iss 1 (2024)
ABSTRACTFine-scale population estimation (FPE) is crucial for urban management. After training, the bottom-up FPE models can be applied independently of census data. However, given the lack of real fine-scale population data, the existing bottom-up m
Externí odkaz:
https://doaj.org/article/bd1e6e39dfc041aaae53c071f37466ea
Autor:
Dan Han, Hao Li, Xin Zheng, Shenbo Fu, Ran Wei, Qian Zhao, Chengxin Liu, Zhongtang Wang, Wei Huang, Shaoyu Hao
Publikováno v:
Frontiers in Immunology, Vol 15 (2024)
ObjectiveDevelop a predictive model utilizing weakly supervised deep learning techniques to accurately forecast major pathological response (MPR) in patients with resectable non-small cell lung cancer (NSCLC) undergoing neoadjuvant chemoimmunotherapy
Externí odkaz:
https://doaj.org/article/3f657eb1dca74a938e52617a1ee4caa7
Publikováno v:
International Journal of Applied Earth Observations and Geoinformation, Vol 133, Iss , Pp 104085- (2024)
Automatic crop mapping is essential for various agricultural applications. Although fully convolutional networks (FCNs) have shown effectiveness in crop mapping, they rely on labor-intensive pixel-level annotations. Weakly supervised semantic segment
Externí odkaz:
https://doaj.org/article/61c23912ca014c708f4905cacd255d2d
Autor:
Rukhma Aftab, Qiang Yan, Juanjuan Zhao, Gao Yong, Yue Huajie, Zia Urrehman, Faizi Mohammad Khalid
Publikováno v:
Frontiers in Oncology, Vol 14 (2024)
IntroductionPathologists rely on whole slide images (WSIs) to diagnose cancer by identifying tumor cells and subtypes. Deep learning models, particularly weakly supervised ones, classify WSIs using image tiles but may overlook false positives and neg
Externí odkaz:
https://doaj.org/article/3a0f00d608504b21a5e51bd6d9d1b891
Autor:
Gang Xu, Shuhao Wang, Lingyu Zhao, Xiao Chen, Tongwei Wang, Lang Wang, Zhenwei Luo, Dahan Wang, Zewen Zhang, Aijun Liu, Wei Ba, Zhigang Song, Huaiyin Shi, Dingrong Zhong, Jianpeng Ma
Publikováno v:
Advanced Intelligent Systems, Vol 6, Iss 8, Pp n/a-n/a (2024)
Histopathology image analysis plays a crucial role in cancer diagnosis. However, training a clinically applicable segmentation algorithm requires pathologists to engage in labor‐intensive labeling. In contrast, weakly supervised learning methods, w
Externí odkaz:
https://doaj.org/article/61afbc3da5814148bcb2298cac4d420b
Publikováno v:
International Journal of Applied Earth Observations and Geoinformation, Vol 132, Iss , Pp 104054- (2024)
Shallow-water benthic habitat classification of coral reefs based on satellite remote sensing is an important part of coral reef monitoring. Leveraging its potent capacity for feature learning, and generalization, deep learning emerges as a robust me
Externí odkaz:
https://doaj.org/article/84fce8e5cb284931b3c5a244f54b46c7