Radar Signal Recognition Based on Squeeze-and-Excitation Networks
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Hao Su | Shunjun Wei | Jun Shi | Qizhe Qu | Mou Wang | Xiaojun Hao
[1] Enhua Wu,et al. Squeeze-and-Excitation Networks , 2017, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[2] Masaaki Kobayashi,et al. Improved algorithm for estimating pulse repetition intervals , 2000, IEEE Trans. Aerosp. Electron. Syst..
[3] Fanji Gu,et al. A new computational model of retinal ganglion cell receptive fields.I.A model of ganglion cell receptive fields with extended disinhibitory area , 2000 .
[4] Berkman Sahiner,et al. Classification of mass and normal breast tissue: a convolution neural network classifier with spatial domain and texture images , 1996, IEEE Trans. Medical Imaging.
[5] H. K. Mardia. New techniques for the deinterleaving of repetitive sequences , 1989 .
[6] Yee Whye Teh,et al. A Fast Learning Algorithm for Deep Belief Nets , 2006, Neural Computation.
[7] Lifen Wang,et al. Weighted Kalman filter phase unwrapping algorithm based on inSAR image , 2013 .
[8] Jian Sun,et al. Deep Residual Learning for Image Recognition , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[9] Jimmy Ba,et al. Adam: A Method for Stochastic Optimization , 2014, ICLR.
[10] Gong Jian,et al. An Improved Algorithm for Deinterleaving of Radar Pulses , 2001 .
[11] H. Robbins. A Stochastic Approximation Method , 1951 .
[12] Geoffrey E. Hinton,et al. Deep Boltzmann Machines , 2009, AISTATS.
[13] Mao Yan. Realization of Radar Pulse Sequence Synthesis Sorting , 2006 .