A survey of FPGA-based accelerators for convolutional neural networks

By Sparsh Mittal. Neural computing & applications (Print), 2018

363 citations recorded by the source corpus.

Subfields: Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/5931c660ea49b3a06fdbc61fdb5e4501729803bd

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Electrical and Electronic Engineering

1. Bashir I. Morshed
2. Syed Kamrul Islam
3. Jianlin Cheng
4. Md Maruf Hossain Shuvo

Citations in the corpus

• Efficient Acceleration of Deep Learning Inference on Resource-Constrained Edge Devices: A Review (2023, methodology): “FPGA-based acceleration of DL tensor computation [11] and execution of compact networks on FPGA [12] are also studied.”