Event-based vision has emerged as a promising paradigm for energy-aware artificial intelligence (AI), offering sparse, low-latency visual signals that reduce redundant data processing and support sustainable edge computing. However, the asynchronous and noise-prone nature of event streams creates challenges for convent...
Riadul Islam, Joey Mulé, Dhandeep Challagundla et al.· IEEE Canadian Journal of Ele...· 0 citations
This work contributes a 2nd-order adaptive LIF neuron with two-stage synaptic filtering for richer temporal dynamics; a fully connected six-neuron spiking network with configurable weights demonstrating weight-based inter-neuron communication; and a direct verification methodology enabling per-cycle observation of all...
A 2nd-order neuron with two-stage synaptic filtering for richer temporal dynamics; a fully-connected 6-neuron spiking network with configurable weights demonstrating weight-based inter-neuron communication; and a direct verification methodology enabling per-cycle observation of all internal states are contributed.
A compact and configurable event-driven autoencoder that efficiently compresses neuromorphic data while preserving essential spatiotemporal structure for downstream inference and demonstrates the potential of compact event-driven models to advance environmentally conscious, low-power AI systems for high-speed perceptio...
Riadul Islam, Joey Mulé, Dhandeep Challagundla et al.· 0 citations
Results show that STGen provides a scalable and reproducible bridge between lightweight protocol emulation and practical deployment-oriented IoT protocol evaluation, and exposes deployment-relevant behavior that controlled emulation alone may hide.
H. Islam, M. M. Maharaz, M. Georgiades et al.· Journal of Sensor and Actuat...· 0 citations
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