Fast Fourier Transformation for Optimizing Convolutional Neural Networks in Object Recognition

10/08/2020
by   Varsha Nair, et al.
134

This paper proposes to use Fast Fourier Transformation-based U-Net (a refined fully convolutional networks) and perform image convolution in neural networks. Leveraging the Fast Fourier Transformation, it reduces the image convolution costs involved in the Convolutional Neural Networks (CNNs) and thus reduces the overall computational costs. The proposed model identifies the object information from the images. We apply the Fast Fourier transform algorithm on an image data set to obtain more accessible information about the image data, before segmenting them through the U-Net architecture. More specifically, we implement the FFT-based convolutional neural network to improve the training time of the network. The proposed approach was applied to publicly available Broad Bioimage Benchmark Collection (BBBC) dataset. Our model demonstrated improvement in training time during convolution from 600-700 ms/step to 400-500 ms/step. We evaluated the accuracy of our model using Intersection over Union (IoU) metric showing significant improvements.

READ FULL TEXT

page 7

page 8

page 9

research
01/25/2016

Very Efficient Training of Convolutional Neural Networks using Fast Fourier Transform and Overlap-and-Add

Convolutional neural networks (CNNs) are currently state-of-the-art for ...
research
02/18/2020

Computational optimization of convolutional neural networks using separated filters architecture

This paper considers a convolutional neural network transformation that ...
research
11/25/2020

Deep Convolutional Neural Networks: A survey of the foundations, selected improvements, and some current applications

Within the world of machine learning there exists a wide range of differ...
research
05/18/2018

Butterfly-Net: Optimal Function Representation Based on Convolutional Neural Networks

Deep networks, especially Convolutional Neural Networks (CNNs), have bee...
research
07/18/2022

SelectionConv: Convolutional Neural Networks for Non-rectilinear Image Data

Convolutional Neural Networks have revolutionized vision applications. T...
research
12/03/2017

Automatic Recognition of Coal and Gangue based on Convolution Neural Network

We designed a gangue sorting system,and built a convolutional neural net...
research
04/14/2022

Learning Convolutional Neural Networks in the Frequency Domain

Convolutional neural network (CNN) has achieved impressive success in co...

Please sign up or login with your details

Forgot password? Click here to reset