Efficient Two-Stage Max-Pooling Engines for an FPGA-Based Convolutional Neural Network

Efficient Two-Stage Max-Pooling Engines for an FPGA-Based Convolutional Neural Network

This paper proposes two max-pooling engines, named the RTB-MAXP engine and the CMB-MAXP engine, with a scalable window size parameter for FPGA-based convolutional neural network (CNN) implementation. The max-pooling operation for the CNN can be decomposed into two stages, i.e., a horizontal axis max...

Full description

Bibliographic Details
Main Authors: Eonpyo Hong, Kang-A Choi, Jhihoon Joo
Format: Article
Language:English
Published: MDPI AG 2023-09-01
Series:Electronics
Subjects:
max pooling
convolutional neural network (CNN)
FPGA
rank-tracking-based max pooling (RTB-MAXP)
cascaded maximum based max pooling (CMB-MAXP)
Online Access:https://www.mdpi.com/2079-9292/12/19/4043

Internet

https://www.mdpi.com/2079-9292/12/19/4043

Similar Items