Essay On Image Classification

Better Essays
Image classification makes use of analyzing various properties of various image features and then sets the data into classes. Classification methods typically uses two levels for the process of classification: training and testing. Primarily in the training phase, characteristics of the image features are extracted and, based on these, a unique description of each classification category, i.e. training class, is created\cite{mohri2012foundations}. In the subsequent testing phase, these feature-space partitions are used to classify image features.\\ Since this task of recognizing a visual concept is relatively trivial for a human to perform,there are several challenges,as follows, to overcome in order to create a perfect classifier.\\…show more content…
In my particular project I'm using Convolution neural network for image classification. \newpage \subsection{CNN for image classification} Convolutional Neural Networks are very similar to ordinary Neural Networks from the previous chapter: they are made up of neurons that have learnable weights and biases. Each neuron receives some inputs, performs a dot product and optionally follows it with a non-linearity. \\Neural Networks receive an input (a single vector), and transform it through a series of hidden layers. The last fully-connected layer is called the “output layer” and in classification settings it represents the class scores. \\ We use three main types of layers to build ConvNet architectures: Convolutional Layer, Pooling Layer, and Fully-Connected Layer (exactly as seen in regular Neural Networks). We will stack these layers to form a full ConvNet architecture.\cite{krizhevsky2012imagenet}\\ INPUT will hold the raw pixel values of the image\\ CONV layer will compute the output of neurons that are connected to local regions in the input, each computing a dot product between their weights and a small region they are connected to in the input volume.\\ RELU layer will apply an elementwise activation function, such as the max(0,x) \\ POOL layer will perform a downsampling operation along the spatial dimensions (width, height)\\ FC (i.e.
Get Access