Subset-Selection Weight Post-Training Quantization Method for Learned Image Compression Task

Post-training quantization(PTQ) has been widely studied in recent years because it does not require retraining the network or the entire training dataset. However, naively applying the PTQ method to quantize low-level image tasks such as learned image compression(LIC) usually incurs significant accu...

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Principais autores:	Jinru Yang, Xiaoqin Wang, Qiang Li, Shushan Qiao, Yumei Zhou
פורמט:	Artigo
שפה:	Inglês
יצא לאור:	IEEE 2025-01-01
סדרה:	IEEE Access
נושאים:	Convolutional neural network post-training quantization non-uniform quantization learned image compression
גישה מקוונת:	https://ieeexplore.ieee.org/document/10819398/
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