James Imber, Director of Research at Imagination Technologies presents “Self-Compression for Edge Inference” at the May 2026 Embedded Vision Summit. Self-compression is a quantization-aware training technique to reduce neural network size and optimize performance for edge inference. By learning optimal bit depths for weights and activations during training, self-compression achieves…
“Self-Compression for Edge Inference,” a Presentation from Imagination Technologies
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