DEEP JOINT TRANSMISSION-RECOGNITION FOR POWER-CONSTRAINED IOT DEVICES
该文提出了将深度信源信道联合编码（JSCC）与网络修剪相结合，并将其应用于无线网络上的图像分类。主要创新点是在JSCC上引入了网络修剪。 主要解决的问题： 1、minimizing the number of computations that have to be done locally； 2、designing a robust communication scheme within th
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相关文章
- 1. Joint Transmission Map Estimation and Dehazing using Deep Networks
- 2. DeepID2：Deep Learning Face Representation by Joint Identification-Verification
- 3. DeepID2 "Deep Learning Face Representation by Joint Identification-Verification"
- 4. DeepRebirth: Accelerating Deep Neural Network Execution on Mobile Devices
- 5. (2020)Deep Joint Entity Disambiguation with Local Neural Attention论文笔记
- 6. 论文阅读：Deep Joint Rain Detection and Removal from a Single Image
- 7. DDNN：Distributed Deep Neural Networks over the Cloud,the Edge and End Devices
- 8. WCID Devices -- Windows Compatible ID Devices
- 9. 【论文阅读】Deep Joint Rain Detection and Removal from a Single Image
- 10. 文章浅析-《Joint Deep Modeling of Users and Items Using Reviews for Recommendation》