Inter-Layer Hybrid Quantization Scheme for Hardware Friendly Implementation of Embedded Deep Neural Networks

Author:

Nazari Najmeh1ORCID,Salehi Mostafa E.1ORCID

Affiliation:

1. University of Tehran, Tehran, Iran

Publisher

ACM

Reference19 articles.

1. RMSMP: A Novel Deep Neural Network Quantization Framework with Row-wise Mixed Schemes and Multiple Precisions

2. Mix and Match: A Novel FPGA-Centric Deep Neural Network Quantization Framework

3. Jungwook Choi , Zhuo Wang , Swagath Venkataramani , Pierce I-Jen Chuang , Vijayalakshmi Srinivasan, and Kailash Gopalakrishnan. 2018 . Pact : Parameterized clipping activation for quantized neural networks. arXiv preprint arXiv:1805.06085 (2018). Jungwook Choi, Zhuo Wang, Swagath Venkataramani, Pierce I-Jen Chuang, Vijayalakshmi Srinivasan, and Kailash Gopalakrishnan. 2018. Pact: Parameterized clipping activation for quantized neural networks. arXiv preprint arXiv:1805.06085 (2018).

4. Deep Residual Learning for Image Recognition

5. Learning to Quantize Deep Networks by Optimizing Quantization Intervals With Task Loss

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