State Classification of Cooking Objects Using a VGG CNN
This is an incremental domain-specific problem for robotics in cooking tasks.
The paper tackled the problem of recognizing cooking object states using a VGG CNN for robot applications, but the abstract does not provide concrete results or numbers.
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.