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Author

Rachit Saini

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2026

Lightweight Autoencoder for Event-Based Vision on Low-Latency Energy-Constrained Edge Devices

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. · 0 citations
#edge computing Preprint Aug 2026

LiteEvent-AE: Lightweight Autoencoder for Event-Based Vision on Low-Latency Energy-Constrained Edge Devices

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

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