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STDP Based Pruning of Connections and Weight Quantization in Spiking Neural Networks for Energy Efficient Recognition
Nitin Rathi, Priyadarshini Panda, Kaushik Roy
Spiking Neural Networks (SNNs) with a large number of weights and varied weight distribution can be difficult to implement in emerging in-memory computing hardware due to the limit…
Gabor Filter Assisted Energy Efficient Fast Learning Convolutional Neural Networks
Syed Shakib Sarwar, Priyadarshini Panda, Kaushik Roy
Convolutional Neural Networks (CNN) are being increasingly used in computer vision for a wide range of classification and recognition problems. However, training these large networ…
Convolutional Spike Timing Dependent Plasticity based Feature Learning in Spiking Neural Networks
Priyadarshini Panda, Gopalakrishnan Srinivasan, Kaushik Roy
Brain-inspired learning models attempt to mimic the cortical architecture and computations performed in the neurons and synapses constituting the human brain to achieve its efficie…
ASP: Learning to Forget with Adaptive Synaptic Plasticity in Spiking Neural Networks
Priyadarshini Panda, Jason M. Allred, Shriram Ramanathan +1
A fundamental feature of learning in animals is the "ability to forget" that allows an organism to perceive, model and make decisions from disparate streams of information and adap…