Results 41 to 50 of about 11,596,145 (301)

Efficient Multi-Scale Feature Generation Adaptive Network [PDF]

Proceedings of the 30th ACM International Conference on Information & Knowledge Management, 2021
Recently, an early exit network, which dynamically adjusts the model complexity during inference time, has achieved remarkable performance and neural network efficiency to be used for various applications. So far, many researchers have been focusing on reducing the redundancy of input sample or model architecture.
Gwanghan Lee, Minha Kim, Minha Kim, Simon S. Woo   +3 more
openaire   +1 more source

Computational fluid dynamics for dense gas-solid fluidized beds: a multi-scale modeling strategy [PDF]

, 2004
Dense gas–particle flows are encountered in a variety of industrially important processes for large scale production of fuels, fertilizers and base chemicals.
van Sint Annaland, M., Hoef, van der, M.A., Kuipers, J.A.M.; id_orcid, van der Hoef, Martin Anton, van der Hoef, M.A., Kuipers, J.A.M., Sint Annaland, van, M.   +6 more
core   +2 more sources

Multi-Scale Modelling of Sintering

, 2008
Multi-scale modelling of ...
Ruo Yu Huang, R Huang (4235968), Jing Zhe Pan, Jingzhe Pan (7212152)   +3 more
core   +7 more sources

Multi-scale modeling of dispersed gas-liquid two-phase flow [PDF]

, 2004
In this work the concept of multi-scale modeling is demonstrated. The idea of this approach is to use different levels of modeling, each developed to study phenomena at a certain length scale.
van Sint Annaland, M., Kuipers, J.A.M.; id_orcid, Kuipers, JAM Hans, Deen, N.G., Deen, NG Niels, Sint Annaland, M Martin van, Kuipers, J.A.M., Sint Annaland, van, M., Deen, N.G.; id_orcid   +8 more
core   +1 more source

Revisiting Multi-Scale Feature Fusion for Semantic Segmentation

CoRR, 2022
It is commonly believed that high internal resolution combined with expensive operations (e.g. atrous convolutions) are necessary for accurate semantic segmentation, resulting in slow speed and large memory usage. In this paper, we question this belief and demonstrate that neither high internal resolution nor atrous convolutions are necessary.
Tianjian Meng, Golnaz Ghiasi, Reza Mahjourian, Quoc V. Le, Mingxing Tan   +4 more
openaire   +2 more sources

Details of our multi-scale spatial focus features enhancement strategy.

, 2022
The input of the module is the output of the last convolutional layer. First, a soft attention mechanism with SPP is used to obtain the multi-scale spatial features.
Guoan Yang (602228), Junjie Yang (219166), Deyang Liu (12256569), Zhengzhi Lu (9239430), Yong Yang (63842), Zien Fan (12256575), Chuanbo Zhou (12256572)   +6 more
core   +1 more source

Concurrent multi-scale modeling of granular materials: Role of coarse-graining in FEM-DEM coupling [PDF]

, 2023
The finite element method (FEM) is commonly used for modeling continuum media, while particle simulation methods like the so-called discrete element method (DEM) are used for discrete systems.
Cheng, Hongyang, Hazel, Andrew L., Cheng, Hongyang; id_orcid, Thornton, Anthony R., Weinhart, Thomas, Luding, Stefan, Weinhart, Thomas; id_orcid   +6 more
core   +2 more sources

Multiplexing Multi-Scale Features Network for Salient Target Detection

Applied Sciences
This paper proposes a multiplexing multi-scale features network (MMF-Network) for salient target detection to tackle the issue of incomplete detection structures when identifying salient targets across different scales.
Xiaoxuan Liu, Yanfei Peng, Gang Wang, Jing Wang   +3 more
doaj   +1 more source

MBMF: Constructing memory banks of multi‐scale features for anomaly detection

IET Computer Vision
In industrial manufacturing, how to accurately classify defective products and locate the location of defects has always been a concern. Previous studies mainly measured similarity based on extracting single‐scale features of samples. However, only using
Yanfeng Sun, Haitao Wang, Yongli Hu, Huajie Jiang, Baocai Yin   +4 more
doaj   +1 more source

Multi-Scale Adversarial Feature Learning for Saliency Detection [PDF]

Symmetry, 2018
Previous saliency detection methods usually focused on extracting powerful discriminative features to describe images with a complex background. Recently, the generative adversarial network (GAN) has shown a great ability in feature learning for synthesizing high quality natural images.
Dandan Zhu, Lei Dai, Ye Luo, Guokai Zhang, Xuan Shao, Laurent Itti, Jianwei Lu   +6 more
openaire   +1 more source