Results 241 to 250 of about 24,894,856 (287)

A Multi-Modal Fusion Network of Visible-Ultraviolet Features for Detecting Aero-Engine Blade Microcracks. [PDF]

Sensors (Basel)
Wang X, Li C, Wei X, He W, Wang Z, Yin Y, Liu W, Wang L.   +7 more
europepmc   +1 more source

Genetic Diversity and Population Structure of Urban and Rural Goshawks. [PDF]

Ecol Evol
Kekkonen JA, Solonen T.
europepmc   +1 more source

An improved nnUNet with Axial Attention Mechanism and Attention Gated Units for Efficient and Accurate Kidney Segmentation in CT Images. [PDF]

Med Phys
Tan M, Jin R, Xu X, Song E.
europepmc   +1 more source

MSA U-Net: a multi-scale attention-enhanced network for automatic segmentation of uterine lymph nodes in MRI images. [PDF]

J Egypt Natl Canc Inst
Hong J, Chen C, Qiu J, Lin Z, Xie Y, Lin Y.   +5 more
europepmc   +1 more source

The information bottleneck method in communications

, 2020
Die Information Bottleneck Methode ist ein informationstheoretisches Verfahren, welches auf die Kompression einer beobachteten Zufallsvariable abzielt. Das wichtigste Ziel dieser Kompression ist die Erhaltung sogenannter relevanter Information. Die Methode hat ihren Ursprung im Maschinenlernen und bisher existieren nur wenige Anwendungen der Methode in
Lewandowsky, Jan
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Hierarchical clustering based on the information bottleneck method using a control process

Pattern Analysis and Applications, 2015
This work was supported by the Spanish Government (Grant No. TIN2013-47276-C6-1-R) and by the Catalan Government (Grant No. 2014-SGR-1232)
Ester Bonmati, Anton Bardera, Imma Boada, Miquel Feixas, Mateu Sbert   +4 more
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Unsupervised object category discovery via information bottleneck method

Proceedings of the 18th ACM international conference on Multimedia, 2010
We present a novel approach to automatically discover object categories from a collection of unlabeled images. This is achieved by the Information Bottleneck method, which finds the optimal partitioning of the image collection by maximally preserving the relevant information with respect to the latent semantic residing in the image contents.
Zhengzheng Lou, Yangdong Ye, Dong Liu
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A Variational Information Bottleneck Method for Network Intrusion Detection

Journal of Communications, 2022
The increasing application of machine learning to network intrusion detection has shown great successes in the recent years. To reduce the high dimension of captured network records for classifiers to learn efficiently, various feature reduction methods have been proposed. Using the Information Bottleneck framework, a concise and discriminative feature
Vu Van Thieu, Nguyen The Anh, Tran Hoang Hai   +2 more
openaire   +2 more sources