Introduction Super Resolution is the process of recovering a High Resolution (HR) image from a given Low Resolution (LR) image. An image may have a “lower resolution” due to a smaller spatial resolution (i.e. size) or due to a result of degradation (such as blurring). We can relate the HR and LR images through the following equation: [latex]LR = … [Read more...] about An Introduction to Super Resolution Using Deep Learning
An In-Depth Guide To Generative Adversarial Networks (GANs)
Generative Adversarial Networks are a powerful class of neural networks with remarkable applications. They essentially consist of a system of two neural networks — the Generator and the Discriminator — dueling each other. Given a set of target samples, the Generator tries to produce samples that … [Read more...] about An In-Depth Guide To Generative Adversarial Networks (GANs)
A Simple Guide to Semantic Segmentation
Semantic Segmentation is the process of assigning a label to every pixel in the image. This is in stark contrast to classification, where a single label is assigned to the entire picture. Semantic segmentation treats multiple objects of the same class as a single entity. On the other hand, instance segmentation treats multiple objects of the same class as distinct individual … [Read more...] about A Simple Guide to Semantic Segmentation