State Classification of Cooking Objects Using a VGG CNN

04/21/2019
by   Kyle Mott, et al.
0

In machine learning, it is very important for a robot to know the state of an object and recognize particular desired states. This is an image classification problem that can be solved using a convolutional neural network. In this paper, we will discuss the use of a VGG convolutional neural network to recognize those states of cooking objects. We will discuss the uses of activation functions, optimizers, data augmentation, layer additions, and other different versions of architectures. The results of this paper will be used to identify alternatives to the VGG convolutional neural network to improve accuracy.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
06/16/2019

Equivariant neural networks and equivarification

We provide a process to modify a neural network to an equivariant one, w...
research
05/23/2018

Classifying cooking object's state using a tuned VGG convolutional neural network

In robotics, knowing the object states and recognizing the desired state...
research
05/13/2019

Joint Object and State Recognition using Language Knowledge

The state of an object is an important piece of knowledge in robotics ap...
research
04/20/2020

Improving correlation method with convolutional neural networks

We present a convolutional neural network for the classification of corr...
research
12/15/2016

Design of Image Matched Non-Separable Wavelet using Convolutional Neural Network

Image-matched nonseparable wavelets can find potential use in many appli...
research
05/25/2017

Classification of Quantitative Light-Induced Fluorescence Images Using Convolutional Neural Network

Images are an important data source for diagnosis and treatment of oral ...
research
02/15/2018

Image Dataset for Visual Objects Classification in 3D Printing

The rapid development in additive manufacturing (AM), also known as 3D p...

Please sign up or login with your details

Forgot password? Click here to reset