PIPPON: Improve Impedance Prediction of Power Distribution Network Using Pole Proposal Network

Author:

Lu Cheng-Hsueh1,Tseng Ling-Yu1,Chang Shih-Chieh1,Wu Shih-Hsien2

Affiliation:

1. National Tsing Hua University,Department of Computer Science,Hsinchu,Taiwan,R.O.C,300

2. Industrial Technology Research Institute,Electronic and Optoelectronic System Research Laboratories,Hsinchu,Taiwan,R.O.C,310

Publisher

IEEE

Reference16 articles.

1. Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks

2. Fast R-CNN

3. Empirical evaluation of rectified activations in convolutional network;xu;arXiv 2015 arXiv 1505 00853,0

4. Batch normalization: Accelerating deep network training by reducing internal covariate shift;sergey;In Proceedings of the International Conference on Machine Learning,2015

5. Efficient DC and AC Impedance Calculation for Arbitrary-Shape and Multilayer PDN Using Boundary Integration

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