Log In Sign Up

Inspect Transfer Learning Architecture with Dilated Convolution

by   Syeda Noor Jaha Azim, et al.

There are many award-winning pre-trained Convolutional Neural Network (CNN), which have a common phenomenon of increasing depth in convolutional layers. However, I inspect on VGG network, which is one of the famous model submitted to ILSVRC-2014, to show that slight modification in the basic architecture can enhance the accuracy result of the image classification task. In this paper, We present two improve architectures of pre-trained VGG-16 and VGG-19 networks that apply transfer learning when trained on a different dataset. I report a series of experimental result on various modification of the primary VGG networks and achieved significant out-performance on image classification task by: (1) freezing the first two blocks of the convolutional layers to prevent over-fitting and (2) applying different combination of dilation rate in the last three blocks of convolutional layer to reduce image resolution for feature extraction. Both the proposed architecture achieves a competitive result on CIFAR-10 and CIFAR-100 dataset.


Pay Attention to Convolution Filters: Towards Fast and Accurate Fine-Grained Transfer Learning

We propose an efficient transfer learning method for adapting ImageNet p...

Convolutional Neural Networks with Layer Reuse

A convolutional layer in a Convolutional Neural Network (CNN) consists o...

Using UNet and PSPNet to explore the reusability principle of CNN parameters

How to reduce the requirement on training dataset size is a hot topic in...

Multi-Subspace Neural Network for Image Recognition

In image classification task, feature extraction is always a big issue. ...

A Genetic Programming Approach to Designing Convolutional Neural Network Architectures

The convolutional neural network (CNN), which is one of the deep learnin...

Exploiting Fully Convolutional Network and Visualization Techniques on Spontaneous Speech for Dementia Detection

In this paper, we exploit a Fully Convolutional Network (FCN) to analyze...

Towards Efficient Convolutional Neural Network for Domain-Specific Applications on FPGA

FPGA becomes a popular technology for implementing Convolutional Neural ...