WebAn unsupervised segmentation method based on dynamic threshold neural P systems for color images. Yulong Cai, Siheng Mi, Jiahao Yan, Hong Peng and Xiaohui Luo et al. 1 Mar 2024 Information Sciences, Vol. 587. A Deep Probabilistic Sensing and Learning Model for Brain Tumor Classification With Fusion-Net and HFCMIK Segmentation.

Dynamic threshold neural P systems - us

WebDynamic threshold neural P (DTNP) systems are a recently de- veloped distributed parallel neural-like computing model [12], in- corporating the spiking mechanism and dynamic threshold mech- anism. Our previous work demonstrated that DTNP systems are Turing-universal computing devices. This paper focuses on the ap- WebDec 31, 2024 · Inspired from intersecting cortical model, this paper proposes a new kind of neural-like P systems, called dynamic threshold neural P systems (for short, DTNP … g04s metal j04c metal

Medical image fusion based on DTNP systems and Laplacian pyramid …

WebOct 23, 2024 · Inspired by Eckhorn's neuron model that emulates a mammal's visual cortex, this paper proposes a new kind of neural-like P system, called a coupled neural P (CNP) system. The CNP system consists of some coupled neurons, each with three components: receptive field, modulation, and output module. CNP systems are a kind of distributed … WebDec 31, 2024 · Inspired from intersecting cortical model, this paper proposes a new kind of neural-like P systems, called dynamic threshold neural P systems (for short, DTNP systems). DTNP systems can be represented as a directed graph, where nodes are dynamic threshold neurons while arcs denote synaptic connections of these neurons. … WebTo address these shortcomings, this paper proposes a neural-like computing model, called dynamic threshold neural P systems with orientation, termed as ODTNP systems. In addition to the spiking and dynamic threshold mechanisms, ODTNP systems also integrate the gradient magnitude and gradient direction information. The combination of … attorney amy johnson