A large feature set was derived from each of these four modalities and a two-level fusion method was developed: Logistic regression (LR) as 'feature-level fusion' and the neural-network (NN) method for higher level fusion.
One of the main challenges of designing higher level fusion processes is to provide a formal structure of domain-specific types of entities, attributes, situations, and the relations between them for reasoning about situations and threats.
The purpose of higher level fusion is to produce contextual understanding of the states of the environment and prediction of their impact in relation to specific goals of decision makers.
The main focus of this paper is to provide a conceptual framework for formally capturing various sorts of complex relation-types, which can serve as a means for a more thorough decomposition of objects, attributes/properties, events, processes, and relations, necessary for higher level fusion processing.
Intelligence applications exploit heterogeneous data using High-Level fusion systems to gain information superiority.
Whereas Low-Level fusion systems have well established frameworks, High-Level fusion has not yet achieved the same level of maturity.
This paper presents a methodology and the underlying architectural components necessary to implement a unified High-Level fusion intelligence application, followed by a case study that demonstrates the resulting improvements in knowledge discovery and predictive accuracy.
Data fusion (low-level fusion) merges several raw signals prior to analysis, while decision fusion (high-level fusion) acts as a post-processor to merge the results of individual data analyses.
High levels of fusion proteins were obtained, constituting 50 58% of total bacterial proteins.
Underweight men showed a "defensive but active" pattern, expressing high avoidance on multiple dimensions, high levels of fusion, but also showing high hope and willingness to experience distress when pursuing goals.
These high levels of fusion protein accumulation in PBs suggest that in addition to organellar sequestration, Zera protein condensation may also provide a mechanism for such fusions to evade the normal ER degradative pathways.
