LSTM-SNP model is a recently developed long short-term memory (LSTM) network, which is
inspired from the mechanisms of spiking neural P (SNP) systems. In this paper, LSTM-SNP …

Gated spiking neural P (GSNP) model is a recently developed recurrent-like network, which
is abstracted by nonlinear spiking mechanism of nonlinear spiking neural P systems. In this …

As an essential step in the early diagnosis of retinopathy, the blood vessels morphological
attributes assist specialists to obtain pathological information efficiently. Most existing deep …

NSNP-type neuron is a new type of neuron model inspired by nonlinear spiking
mechanisms in nonlinear spiking neural P systems. In order to address the loss problem of …

Spiking neural P (SNP) systems are a class of distributed and parallel neural-like computing
models that are inspired by the mechanism of spiking neurons and are 3rd-generation …

Nonlinear spiking neural P (NSNP) systems are one of neural-like membrane computing
models, abstracted by nonlinear spiking mechanisms of biological neurons. NSNP systems …

Nonlinear spiking neural P (NSNP) systems are neural-like membrane computing models
with nonlinear spiking mechanisms. Because of this nonlinear spiking mechanism, NSNP …

Radiotherapy is one of the leading treatments for cancer. To accelerate the implementation
of radiotherapy in clinic, various deep learning-based methods have been developed for …

To solve the challenges of low recognition accuracy, slow speed, and weak generalization
ability inherent in traditional methods for multi‐damage recognition of concrete bridges, this …

Magnetic Resonance Imaging (MRI) is an important diagnostic technique for brain tumors
due to its ability to generate images without tissue damage or skull artifacts. Therefore, MRI …