Insect-Inspired Visual Guidance: are current familiarity-based models ready for long-ranged navigation?

Insects have — over millions of years of evolution — perfected many of the systems that roboticists aim to achieve; they can swiftly and robustly navigate through different environments under various conditions while at the same time being highly energy efficient. To reach this level of performance and efficiency one might want to look at and take...

An Object Detecting Architecture using Spiking Neural Networks

Spiking Neural Networks have opened new doors in the world of Neural Networks. This study implements and shows a viable architecture to detect and classify blob-like input data. An architecture consisting of three parts a region proposal network, weight calculations, and the classifier is discussed and implemented. The region proposal network is...

N-shot Training Methodology: For Spiking Neural Networks(SNNs)

Traditional Artificial Neural Networks(ANNs)like CNNs have shown tremendous opportunities in various domains like autonomous cars, disease diagnosis, etc. Proven learning algorithms like backpropagation help ANNs in achieving higher accuracy. But there is a serious challenge with the increasing popularity of traditional ANNs is of energy...

A Highly Concurrent, Memory-Efficient AER Architecture for Neuro-Synaptic Spike Routing

One of the challenges of neuromorphic computing is efficiently routing spikes from neurons to their connected synapses. The aim of this thesis is to design a spike-routing architecture for flexible connections on single-chip neuromorphic systems. A model for estimating area, power consumption, memory, spike latency and link utilisation for...