4.2 Intelligent diagnosis through attention based bidirectional recurrent neural networks Currently, as the use of deep learning is relatively new in the field of radiogenomics analysis, a large number of manually labeled data is used. This is resource intensive and impractical. Many current cancer im...
For instance, WPT needs to choose the suitable wavelet kernel function [8] and VMD need to set the penalty factor α and the number of intrinsic mode functions (IMFs) K before processing the vibration signals [10], thereby the self-adaptive capacity of them is poor. EMD enjoys good ...
where machine learning has been demonstrated to be a useful tool [65]. Note that multiscale representations can also be obtained using traditional methods such as wavelets in a more compact manner [64,66]. However, in general, these traditional methods require domain expertise for feature extract...
The usage of discontinuous chopped fibers as reinforcement in cementitious composite materials can yield materials with interesting properties but requires careful attention to mixture design and sample preparation. Parameters such as fiber length and aspect ratio, dispersion and wetting behavior of the fibe...
Our work extends the attention mechanism to the 3D domain to extract multiscale deformation features based on an effective shape representation [19]. 3 DEFORMATION REPRESENTATION AND CONVO- LUTION OPERATOR The input of our overall network is based on the recently proposed as-consistent-as-possible ...
The structure of the attention module based on the ROI is illustrated in Figure 4. Multiscale refers to feature maps of different scales, and different features can be observed at different scales. In neural networks, multiscale can be embodied as scaling the output feature maps of different ...
Local value of h is modernly estimated with Wavelet Theory [39], often using successive derivatives of the Gaussian function as the analyzing wavelet at different scales a, in order to remove polinomial trends with polinomial order up to the wavelet derivative order. In these conditions, the ...
Automated skin lesion segmentation using attention-based deep convolutional neural network. Biomed. Signal Process. Control 2021, 65, 102358. [Google Scholar] [CrossRef] Abbas, Q.; Celebi, M.E.; García, I.F. Hair removal methods: A comparative study for dermoscopy images. Biomed. Signal ...
Spatiotemporal fusion of remote sensing images using a convolutional neural network with attention and multiscale mechanisms. Int. J. Remote Sens. 2021, 42, 1973–1993. [Google Scholar] [CrossRef] Walker, J.; Beurs, K.D.; Wynne, R.; Gao, F. Evaluation of Landsat and MODIS data fusion...
Wavelet transforms: An introduction. Electron. Commun. Eng. J. 1994, 6, 175–186. [Google Scholar] [CrossRef] Yuan, R.; Lv, Y.; Lu, Z.; Li, S.; Li, H. Robust fault diagnosis of rolling bearing via phase space reconstruction of intrinsic mode functions and neural network under ...