4.2 Data fusion Data fusion usually refers to using the multi-channel or multi-sensor datasets at the same time to obtain more accurate analysis results [102,111]. The common theories of data fusion include the Bayesian theory, DS evidence theory, Kalman filter theory, etc. [112]. The Bayes...
The principle of this new approach is to build a speech model in the time鈥揻requency domain using the formalism of dynamic Bayesian networks. In contrast to classical multi-band modeling, this formalism leads to a probabilistic speech model which allows communications between the different sub-...
Needle-in-a-Haystack problems exist across a wide range of applications including rare disease prediction, ecological resource management, fraud detection, and material property optimization. A Needle-in-a-Haystack problem arises when there is an extreme
A data fusion approach to optimize compositional stability of halide perovskites. Matter 4, 1305–1322 (2021). 5. Snelson, E. & Ghahramani, Z. Sparse Gaussian Processes using Pseudo-inputs, vol. 18 (MIT Press, 2005). 6. Rasmussen, C. E. & Williams, C. K. I. Gaussian Processes for...
the fusion protein translocates to the nucleus, allowing chemiluminescent detection. Cells at a range of densities were resuspended in assay buffer into white-tissue culture-treated multi-well plates and increasing concentrations of control compounds were dispensed. The plate was incubated for 3 h at...
Inform. Fusion, 2000. [34] M. Pitt and N. Shephard, "Filtering via simulation: Auxiliary particle filters," J. Amer. Statist. Assoc., vol. 94, no. 446, pp. 590–599, 1999. [35] L. R. Rabiner, "A tutorial on hidden Markov models and selected a...
Image fusion method is suitable for multispectral bands in Bayesian network based on Multiresolution analysis and classification in medical imaging. The Wavelet and Curvelet transform is to represent fused image containing a number of edges and the wavelet transform preserves list of detailed spectral ...
To solve the problems, this paper proposes a dual-band ship decision-level fusion classification method based on multi-layer features and naive Bayesian model. To avoid the occurrence of over-fitting caused by the small number of annotated samples, the proposed method is adopted. First of all,...
[113] CNN Feature-level Multi-modal A two-branch CNN framework is proposed to study classification and fusion of hyperspectral image and other multi-sensor data. [34] CNN Data-level Multi-modal A multi-sensor data fusion method based on convolutional neural network is proposed to learn features...
7.2.2.1 Fusion of one image with prior knowledge In the Bayesian methodology, additional prior knowledge concerning r that is independent of observing d1 should get incorporated into the stochastic model via the prior distribution p(r). By additional prior knowledge we mean prior knowledge that is...