Peer-Reviewed Research
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Quantized Neural Network Architectures for Low-Latency Distributed Inference on Heterogeneous Edge Systems
Deploying modern deep neural networks across resource-constrained edge computing environments requires balancing model inference latency with accuracy and memory bandwidth. In this study, we propose a structured hybrid pruning and mixed-precision integer quantization framework tailored…