Affiliation:
1. NXP Semiconductors, Hamburg, Germany
2. Integrated Digital Systems, ITEM Institute, University of Bremen, Bremen, Germany
Funder
IPCEI ME/CT
European Union Next Generation EU
German Federal Ministry for Economic Affairs and Climate Action
Bavarian Ministry of Economic Affairs, Regional Development and Energy
Free State of Saxony with the Help of Tax Revenue Based on the Budget Approved by the Saxon State Parliament
Free and Hanseatic City of Hamburg
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Reference16 articles.
1. Deep Residual Learning for Image Recognition
2. Quantization and Training of Neural Networks for Efficient Integer-Arithmetic-Only Inference
3. MobileNets: Efficient convolutional neural networks for mobile vision applications;Howard;arXiv:1704.04861,2017
4. Deep compression: Compressing deep neural networks with pruning, trained quantization and Huffman coding;Han;arXiv:1510.00149,2015
5. Low-Power Coding: Trends and New Challenges