… how machine learning can benefit and optimize data fusion. … on data fusion methods based
on machine learning. We first … the background of data fusion and machine learning in terms of …

… Machine learning (ML) methods are fundamental to the phi… , both ML and sensor data fusion
(SDF) took prominence in the … to multimodal analysis and information fusion in the 1990s [2], …

… learning and optimization methods. One of the main goals of … in data fusion and machine
learning for industrial prognosis, … extraction techniques and machine learning methods will be …

… success of Machine Learning along with IOT prove their fusion as the wonderful source in
the field of Data science. This paper discussed the different applications of machine learning …

… an adequate fusion method, we recently proposed a machine-learning data-… fusion method
well for a given data set, making us able to claim a broad generality for our sensor fusion …

… fusion model comprising three machine learning … fusion approach proposed in this paper
involves Support Vector Regression (SVR) in the first stage. The second stage of the fusion …

… known from machine learning domain are used in fusion systems … of learning or adapting
classifiers in a data fusion engine … Similarly to tracking, the feature fusion with classifier requires …

… most important information fusion data-driven algorithms based on Machine Learning (ML) …
This paper produces a thorough review of the latest work on information fusion for Earth …

… architecture, the theoretical and mathematical background of the selected machine learning
classifiers, and the approach to their fusion are also presented in this section. The details of …

… Fusion-based Machine learning … data fusion techniques, the fused Machine learning
method may offer a strong computing ability and prediction. In this scenario, the machine learning…