Author

Suman Kumar

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Preprint Sep 2026

A Reconfigurable Hybrid Convolutional-Fully Connected Neuromorphic Core for Biomedical Edge Inference

This work presents a programmable FPGA-based architecture for spiking convolutional neural network (SCNN) inference, with real-time hypoxia classification serving as a biomedical edge application. The architecture implements a hybrid spiking convolutional-fully connected (CNN-FC) topology on a programmable, quantized,...

Sarah Johari, Suman Kumar, A. Mishra et al. · 0 citations

Open access

Dependable digital spiking neuromorphic hardware

Spiking neural networks (SNNs) are a biologically inspired class of machine learning models in which information is encoded and processed as sparse, asynchronous spike events distributed over time. When mapped onto digital neuromorphic hardware, these networks perform event-driven computation at very low power, making...

Suman Kumar, Nagarajan Kandasamy, Anup Das · 0 citations