IEEE transactions on neural networks and learning systems
Aug 4, 2023
Segmenting breast tumors from dynamic contrast-enhanced magnetic resonance (DCE-MR) images is a critical step for early detection and diagnosis of breast cancer. However, variable shapes and sizes of breast tumors, as well as inhomogeneous background...
IEEE transactions on neural networks and learning systems
Aug 4, 2023
Deep learning (DL) is known for its excellence in feature learning and its ability to deliver high-accuracy results. Its application to ECG biometric recognition has received increasing interest but is also accompanied by several deficiencies. In thi...
IEEE transactions on neural networks and learning systems
Aug 4, 2023
Muscle fatigue detection is of great significance to human physiological activities, but many complex factors increase the difficulty of this task. In this article, we integrate several effective techniques to distinguish muscle states under fatigue ...
IEEE transactions on neural networks and learning systems
Aug 4, 2023
Survival analysis is a critical tool for the modeling of time-to-event data, such as life expectancy after a cancer diagnosis or optimal maintenance scheduling for complex machinery. However, current neural network models provide an imperfect solutio...
IEEE transactions on neural networks and learning systems
Aug 4, 2023
Dendrite morphological neurons (DMNs) are neural models for pattern classification, where dendrites are represented by a geometric shape enclosing patterns of the same class. This study evaluates the impact of three dendrite geometries-namely, box, e...
IEEE transactions on neural networks and learning systems
Jul 6, 2023
Image denoising and classification are typically conducted separately and sequentially according to their respective objectives. In such a setup, where the two tasks are decoupled, the denoising operation does not optimally serve the classification t...
IEEE transactions on neural networks and learning systems
Jul 6, 2023
Noise attenuation is a crucial phase in seismic signal processing. Enhancing the signal-to-noise ratio (SNR) of registered seismic signals improves subsequent processing and, eventually, data analysis and interpretation. In this work, a novel noise r...
IEEE transactions on neural networks and learning systems
Jul 6, 2023
The simultaneous-source technology for high-density seismic acquisition is a key solution to efficient seismic surveying. It is a cost-effective method when blended subsurface responses are recorded within a short time interval using multiple seismic...
IEEE transactions on neural networks and learning systems
Jul 6, 2023
3-D salt segmentation is important for many research topics spanning from exploration geophysics to structural geology. In seismic exploration, 3-D salt segmentation is directly related to the velocity modeling building that affects many processing s...
IEEE transactions on neural networks and learning systems
Jul 6, 2023
Passive seismic interferometry is a vastly generalized blind deconvolution question, where different paths through the Earth correspond to different channels called Green's functions; the sources are completely incoherent and not shared by the channe...