![]() ![]() The width and height are 682 and 400 pixels, respectively. The dimensions of this fruit bowl image are 400 x 682 x 3. These color channels are stacked along the Z-axis. Color images are a 3-Dimensional matrix of red, green, and blue light-intensity values. the width and height.Ĭolor images are constructed according to the RGB model and have a third dimension - depth. Therefore, we can think of the fruit bowl image above as a matrix of numerical values. ![]() An image's pixels are valued between 0 and 255 to represent the intensity of light present. Click here to skip to Keras implementation.ĭigital images are composed of a grid of pixels. The first half of this article is dedicated to understanding how Convolutional Neural Networks are constructed, and the second half dives into the creation of a CNN in Keras to predict different kinds of food images. It is a very popular task that we will be exploring today using the Keras Open-Source Library for Deep Learning. This algorithm attempts| to learn the visual features contained in the training images associated with each label, and classify unlabelled images accordingly. It is a supervised learning problem, wherein a set of pre-labeled training data is fed to a machine learning algorithm. Image Classification attempts to connect an image to a set of class labels. In this article, we will tackle one of the Computer Vision tasks mentioned above, Image Classification. The accessibility of high-resolution imagery through smartphones is unprecedented, and what better way to leverage this surplus of data than by studying it in the context of Deep Learning. The research behind these tasks is growing at an exponential rate, given our digital age. Computer Vision deals in studying the phenomenon of human vision and perception by tackling several 'tasks', to name just a few: Subconsciously taking in information, the human eye is a marvel in itself. We are constantly recognizing, segmenting, and inferring objects and faces that pass our vision. The way in which we perceive the world is not an easy feat to replicate in just a few lines of code. ![]() Computer Vision is a domain of Deep Learning that centers on the fundamental problem in training a computer to see as a human does. There's no shortage of smartphone apps today that perform some sort of Computer Vision task. ![]()
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