SAFE DNN: A Deep Neural Network With Spike Assisted Feature Extraction For Noise Robust Inference
We present a Deep Neural Network with Spike Assisted Feature Extraction (SAFE DNN) to improve robustness of classification under stochastic perturbation of inputs. The proposed network augments a DNN with unsupervised learning of low level features using spiking neural network (SNN) with spike timing dependent plasticity (STDP) The complete network learns to ignore local perturbation while performing global feature detection and classification. The experimental results on CIFAR 10 and ImageNet subset demonstrate improved noise robustness for multiple DNN architectures without sacrificing accuracy on clean images.
2020 International Joint Conference on Neural Networks (IJCNN)