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Found 3 papers, 1 papers with code
Post-Training Piecewise Linear Quantization for Deep Neural Networks
Quantization plays an important role in the energy-efficient deployment of deep neural networks on resource-limited devices.
Accelerating Convolutional Neural Networks via Activation Map Compression
The deep learning revolution brought us an extensive array of neural network architectures that achieve state-of-the-art performance in a wide variety of Computer Vision tasks including among others, classification, detection and segmentation.
Texture Representations for Image and Video Synthesis
In texture synthesis and classification, algorithms require a small texture to be provided as an input, which is assumed to be representative of a larger region to be re-synthesized or categorized.
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