Li et al. (2010) developed the Markov chain models by integrating multi-scale information, such as logging, core data and seismic data.
Our proposed strategy of utilizing multi-scale information is discussed in Section 3. In section 4, we describe our feature processing in detail.
We propose our fine-grained image recognition framework based on FV-CNN and gear it with a novel strategy of utilizing multi-scale information.
Hopefully, the multi-scale information in this work can bring novel insights into the understanding of CIL-catalyzed alkylation and further the design and optimization of this process.
Based on this circumstance, multi-scale information system is introduced by Wu and Leung and extends the theory and application of information system.
Recently, scale selection is the main issue of multi-scale information system, and optimal scale selection is to choose a proper decision table for final decision making or classification.
These composition vectors (CVs) not only add a new direction dimension to the landscape pattern metrics already available, but also provide multi-scale information, i.e. CV at every point and the boundary segment CV BSCVV).
Facing these limitations, we propose to generate multi-scale information by pooling feature tensors of the last convolutional layer with relu activation in a CNN using different pooling window sizes, which is shown in the flowing of part (c) to part (d) in Fig. 1 and more detailed in Fig. 2.
Inheriting from classical bag-of-visual-words model, FV-CNN pools multi-scale information from input image pyramids, i.e., different rescaled versions of a same original image, as shown in the flowing from part (a) to part (c) in Fig. 1.
The VSAXS data were combined with USAXS and SAXS data to provide multi-scale information about the structural organization of cellulosic architecture in maize.
We extract the multi-scale information backbone of the PHPN based on the local densities of the network and discarding weak connection.
