Sentence examples for network recognition from inspiring English sources

Road network recognition approach using image morphological characteristics is proposed by Zhu et al. [26].

These UPOs correspond to network recognition states for these input values.

The need for a novel multi-scale ESD (ElectroStatic Discharge) network recognition and verification methodology is described in this paper.

To enhance the accuracy of the network recognition rate, we studied the impacts of notable network parameters for both learning as well as neuron models.

Based on the experimental results in this work, choosing optimized parameters for learning rate between 0.008 and 0.01, a frequency of input spikes 18 Hz, the sizes of mini-batches between 25 and 50, and two different membrane voltage thresholds for hidden and visible layers leads to the optimum results in the accuracy rate of the network recognition.

Table 7 The average recognition rates of different methods on the CMU-PIE database for face recognition under varying illumination Algorithm FLBP NRLBP++ LG-face W-face G-face BN2 BNR-NetworkoRecognitionion rate 0.5489 0.5744 0.8863 0.8898 0.9093 0.9122 0.9234 0.9378 The bold indicates the best.

In order to overcome some unavoidable factors, like shift of the part, that influence the crisp neural networks' recognition, the present study is dedicated in developing a novel fuzzy neural network (FNN), which integrates both the fuzzy set theory and adaptive resonance theory 2 (ART2) neural network for grouping the parts into several families based on the image captured from the vision sensor.

Opportunities for the community midwifery programme were: a culturally acceptable intervention, deployment of CM to their own community, capacity building, linkage to health facilities, regular reporting and feedback, support from governmental and non-governmental organisations, establishment of social networks, recognition within the community, self-actualisation, vocational and pastoral calling.

The Adoption Access Network suggests recognition of one weak spot — and perhaps the emergence of a generation of women's advocates who want to remedy that.

Neural network pattern recognition opens whole new categories of hitherto insoluble problems.

We therefore identified pillar tip positions by neural network based recognition.