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Conditional Deep Learning for energy-efficient and enhanced pattern recognition.

, , and . DATE, page 475-480. IEEE, (2016)

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Semantic driven hierarchical learning for energy-efficient image classification., and . DATE, page 1582-1587. IEEE, (2017)A Comprehensive Analysis on Adversarial Robustness of Spiking Neural Networks., , , , , and . IJCNN, page 1-8. IEEE, (2019)Attention Tree: Learning Hierarchies of Visual Features for Large-Scale Image Recognition., and . CoRR, (2016)Tree-CNN: A Deep Convolutional Neural Network for Lifelong Learning., , and . CoRR, (2018)STDP Based Pruning of Connections and Weight Quantization in Spiking Neural Networks for Energy Efficient Recognition., , and . CoRR, (2017)Learning to Recognize Actions from Limited Training Examples Using a Recurrent Spiking Neural Model., and . CoRR, (2017)Synthesizing Images from Spatio-Temporal Representations using Spike-based Backpropagation., , and . CoRR, (2019)Discretization Based Solutions for Secure Machine Learning Against Adversarial Attacks., , and . IEEE Access, (2019)FALCON: Feature Driven Selective Classification for Energy-Efficient Image Recognition., , , and . IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 36 (12): 2017-2029 (2017)Beyond classification: directly training spiking neural networks for semantic segmentation., , and . Neuromorph. Comput. Eng., 2 (4): 44015 (December 2022)